In the age of generative artificial intelligence (Gen AI), unvigilant online exams (both closed- and open-book ones) have become obsolete in modern education. Yet some universities continue to pursue graduate assessment based on this exact type of examination.

Well, it wasn’t sufficient for theoretical questions even before the boom of Gen AI or large language models (LLMs) chatbots. But, nowadays, it’s just as irrelevant as you can imagine.

So, I decided to launch an experiment for myself - to virtually recreate one of the recent past exam students undertook for their postgraduate module in financial markets, and pass it. For the purity of an experiment: neither I authored the exam questions, nor have I obtained model answers to them. So, the exam questions were unknown to me, as they were for students.

The final assessment was in the form of an open-book exam that lasted three and a half hours, requiring students to solve three out of six questions of their choice. Each question consisted of three to five sub-questions.

First, I solved the task by myself and took some time to type the answers into the document (as required by the exam requirements).

Then, I got the same questions and uploaded them to LLMs-chatbots to check the answers. No advanced prompt engineering was required to get the correct answer in less than a minute per question. Simply copying and pasting the question perfectly has sufficed. Although the time of response depended on the length of the question that demanded the chatbot to type its chain or tree of thought line by line, it didn’t take more than a minute or so.

As expected, LLMs chatbots were faster. No one confronts the speed of processing the information by LLMs (when no genuine creativity is required), but let’s discuss the consequences for the educational system.

Evidently, in poorly monitored online exams, it takes more time for a diligent student to solve the questions on their own than for a bad actor to use LLM chatbots. However, both students would probably end up with the same grade.

Even a decent student can input exam questions into chatbots to check their own results after the exam. Simply put, students already know the correct answers while they are waiting for the final results.

But why do some universities continue to utilise unvigilant online exams? Apart from the lower costs, it also refers to a lower teaching qualification. In a nutshell, the success of the most decent and talented students depends on the quality of exam questions (e.g. the language and the clarity of the task) along with high teaching quality that preceded the exams. Albeit, the lack in both exam and teaching quality can be overcome by bad actors using LLMs-chatbots.

Some outdated instructions provided for the exam only amplified the confusion. For instance, statements like “use of non-programmable and non-financial electronic calculators is permitted.” For example, to speed up my work, I use Python for calculus, data storage, and processing automation. Thus, it is a genuinely human-created piece of work, not LLM-generated content. In 2025, with ubiquitous programming, these instructions had already lost their relevance.

Such instructions can hardly protect diligent students from bad actors in the context of poorly monitored online exams. Furthermore, it’s not the students’ problem at all. It is the universities’ mission to ensure a healthy environment for equal opportunities and fair grading based on student knowledge and skills, not on LLM chatbots’ evaluation. Students should be able to compete based on their knowledge, not on advancements in prompt engineering or deliberate lack of integrity.

Besides, the job market doesn’t stay still. More companies are coming back to face-to-face interviews - even for internships and placements. So, graduates should be able to prove their knowledge and skills while LLMs-chatbots are turned off.

Grades have always been the primary metric for distinguishing the most talented students. Unfortunately, poorly monitored online exams in the Gen AI era only lead to enormous grade inflation.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 147) by Dr. Olga D. Khon

Grade inflation has become a modern public narrative. Earlier this year, Harvard University published a grading report that exposed the issue of grade inflation within the Ivy League university [1].

The commercial proliferation of generative artificial intelligence (GenAI) has disrupted the marking processes in higher education. While some universities keep up online non-vigilant exams or report/article assignments, the task of talent identification based on grades has turned into an impossible one.

So, can we still effectively distinguish talented youth from bad actors, where nearly everyone has a distinction? Beyond crucial upgrades, the intensive pressure on academic integrity will only amplify. Many experts agree, sitting exams works just fine, but it comes with demands for a greater quality of multidisciplinary education.

However, resistance to implementing feasible changes persists in the educational system. And it’s rooted in the general confusion over different types of AI, their underlying mechanisms and challenges for everyday life, business operations and educational activities.

Let’s address the key pillars to highlight the AI impact on the modern job market and higher education:

1. A computer science degree doesn’t automatically guarantee expertise in AI and Data Science. Basically, it refers to coding and programming knowledge based on a few languages studied. In addition to programming languages, AI engineering expertise requires a profound understanding of AI algorithms (e.g. Machine learning, Reinforcement learning, Deep learning, Natural language processing, Computer vision), the maths behind them, and business applications.

2. Communication with chatbots (sending prompts and getting generated outcomes) is not an AI expertise. The former is an example of passive consumption of AI-generated content that causes diminishing analytical abilities and creative skills.

3. Data is the primary asset. Concerns over personal and business data confidentiality, along with cybersecurity risks, question the ubiquitous usage of GenAI by employees in prominent businesses. Although these entities actively incorporate IT and AI automation, this functionality goes far beyond publicly available GenAI tools (aka chatbots). Besides, professional employers would be rather reluctant for employees to share insightful data with chatbots.

4. A narrow domain of knowledge (in our case, economics and finance) can’t be sufficient for a successful and sustainable career anymore. Deep-dive Interdisciplinarity is at the core of the employability progress. On top of your domain knowledge, it’s recommended to plunge into programming, data science and AI engineering. And it will never be superfluous to evolve in arts, classical music, high literature and modern languages.

Life-long learning stopped being just a fashionable trend; it’s the essence of sustainable development. Let’s hope our society can handle the rising grade inflation before it is doomed by fake education.

References:

[1] Harvard University. “2025 Upgrade on Grading and Workload”. Available at https://oue.fas.harvard.edu/faculty-resources/report-on-grading/

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 146) by Dr. Olga D. Khon

It seems that October 2025 to be remembered by the financial world for the controversy of events that occurred in a single month ever before:

1)Thursday (October 30, 2025) – Amazon’s stock skyrocketed following its third-quarter earnings report, driven by its largest cloud division, Amazon Web Services (AWS), which reported a 20% revenue increase to $33 billion [3]. Many attribute this surge to the ongoing artificial intelligence (AI) boom.

This came shortly after a global AWS outage on October 20, 2025, which disrupted operations for numerous corporations and digital platforms—including Snapchat, Roblox, Fortnite, Signal, Coinbase, Robinhood, Reddit, Lloyds Bank, and others—resulting in significant losses for AWS’s corporate clients [4].

Despite an optimistic earnings report, Amazon has announced (on October 27, 2025) the massive lay-off of 30,000 corporate jobs to be launched in the future [6].

2)Wednesday (October 29, 2025) - For the first time in history, the Fed (Federal Reserve) was forced to decide on interest rates with no official job market data available [5] due to the longest (in the last 50 years) US Government shutdown commenced on October 1, 2025. The Fed cut interest rates to a range of 3.75%–4%, the lowest level in three years, aiming to support employment despite persistent inflation at 3%.

3)Monday (October 27, 2025) – The U.S. national debt reached an all-time high of $38 trillion, increasing by $2 trillion since January 2025 [2].

4)Thursday (October 23, 2025) – It was announced that President Donald J. Trump pardoned convicted felon Changpeng Zhao (CZ), former CEO of Binance crypto exchange [1]. CZ had pleaded guilty to money laundering and was ordered to pay $4.3 billion to the U.S. government after an investigation revealed Binance helped users bypass international sanctions. The pardon sparked a widespread debate over potential conflicts of interest involving President Trump and his family’s apparent ties or intentions to engage with Binance’s crypto business.

In such a rapidly changing environment, our finance students should profoundly understand global financial markets - successfully navigate through the modern AI-driven reality. 

As a result, they are increasingly demanding timely, professional knowledge during their university studies. Today, students value their time more than ever, and university educators must rise to meet these expectations.

References:

[1] BBC ”Trump pardons Binance founder Changpeng Zhao”. Available at https://www.bbc.co.uk/news/articles/cly1qrl9l1qo

[2] CBS News “U.S. debt tops $38 trillion for the first time, worsened by government shutdown”, October 23, 2025. Available at https://www.cbsnews.com/news/us-debt-38-trillion-government-shutdown-2025/

[3] CNBC. “Amazon cloud records 20% sales growth, topping estimates”, October 30, 2025. Available at https://www.cnbc.com/2025/10/30/aws-q3-2025-earnings-report-amazon-cloud.html

[4] CNN “Amazon says systems are back online after global internet outage”, October 21, 2025. Available at https://edition.cnn.com/business/live-news/amazon-tech-outage-10-20-25-intl

[5] Fortune “Powell cuts rates in the dark in historic move, with no jobs data and Trump heckling from abroad”, October 29, 2025. Available at https://fortune.com/2025/10/29/powell-cuts-interest-rates-employment-inflation-trump-incompetent/

[6] Reuters “Exclusive: Amazon targets as many as 30,000 corporate job cuts, sources say”, October 28, 2025. Available at https://www.reuters.com/business/world-at-work/amazon-targets-many-30000-corporate-job-cuts-sources-say-2025-10-27/

[7] Reuters “Global debt hits record of nearly $38 trillion, says IIF”, September 25, 2025. Available at https://www.reuters.com/world/china/global-debt-hits-record-nearly-338-trillion-says-iif-2025-09-25/

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 145) by Dr. Olga D. Khon

Pressure on our students in economics and finance has intensified — from a slowing economy and shrinking job market to generative artificial intelligence (Gen AI) disrupting the remaining career opportunities.

This burden shouldn’t fall solely on the students. It is we, university educators, who bear the responsibility to urgently recalibrate our teaching to meet the demands of the modern world.

And, as always, the emphasis should be placed more deliberately on the in-time, relevant and interdisciplinary educational content, rather than the formality of delivering it.

I once became a witness to an unspoken professional negligence towards the students’ learning about financial markets. In short, there are supposed to be six or seven topics taught each week by different tutors with a final exam at the end. Nothing extraordinary, except that one time (for some undiscovered reasons) the topics were shuffled by accident.

So that students (beginners in financial markets) were taught yield curves, derivative markets, foreign exchange, equity and debt markets along with asset valuation in the first place. And only after that — the existence of commercial and investment banking, and finally — the essence of financial intermediation and financial regulation.

Thus, formally, all the necessary topics were taught. But every finance professional knows we should start with the peculiarity of financial intermediation, commercial and investment banking, and financial regulation, to build the foundation of understanding and knowledge before all the following more advanced topics.

Therefore, such a disrupted topic distribution led to students’ enormous stress, and what is more, could cause hidden discouragement in their studies and life-learning journey. The unforgivable mistake made by formal educators costs a high price paid by students during their precious time at the university.

Fortunately, our students are smart and can cope with such obstacles to successfully pass exams. Nonetheless, they deserve the best educators in the first place.

In the end, student demand for high-profile university education in the age of Gen AI is rising. Educators must be able to provide students with more holistic and thorough knowledge than they could obtain from fragmented Gen AI prompting.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 144) by Dr. Olga D. Khon

Today, data science and data analytics should be an inevitable part of higher education in economics and finance. That said, programming, statistics, and econometrics should be incorporated by default into the core domain of these disciplines.

This is not a tribute to fashion over tradition — It’s an urgent necessity in the modern world of big data and ubiquitous algorithms.

It’s our obligation as educators to our students — to provide them with a university degree that is highly competitive in a rapidly changing job market. Their employment and professional future are at stake.

Now, imagine an undergraduate student entering the classroom for their first research project. What should you consider as an educator?

First and foremost, the data analytics skills you can teach them, right? These transferable skills lie at the heart of their research journey — within the classroom and beyond

In short, they should learn how to conduct professional data storytelling. And every data analyst and data scientist would agree, here is where the Exploratory Data Analysis (EDA) comes. It’s the basic minimum to accomplish. EDA covers both numeric and non-numeric data, and, thanks to advancements in artificial intelligence or AI (please do not limit the term solely to chatbots’ communication), refers to all the areas of quantitative and qualitative research. It’s the foundational background to any data analysis within Academia and the business environment.

And, for sure, students should be taught how to perform EDA with programming languages like Python or R — for their functionality, flexibility and analytical customisation. To answer potential criticism: for starters, they could also learn the Data Analysis Toolkit within MS Excel. Albeit it’s rather inconvenient for big data analytics, and provides a narrow competitive advantage to our students.

Indeed, this education upgrade provision in economics and finance should have been done years before this note’s publication. But let’s hope it’s not too late to catch the train.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 143) by Dr. Olga D. Khon

For centuries Grade-A University Diploma served as a quality label for graduates and their employers around the World. As higher educators, we strive to help our students learn and progress along their university studies.

Unfortunately, the essence of assessment in higher education has changed dramatically in the last three years. And the UK is no exception. This occurred due to the ubiquity of tools known as generative artificial intelligence (GenAI) or, simply put, chatbots based on large language models (LLMs).

While many traditional types of assessment remain unchanged — such as online, non-invigilated open-book exams, articles, and reports — their impact on overall student integrity in the age of GenAI can be detrimental.

Unfortunately, such assessment types do not nourish an equal educational environment for everyone. Where decent and talented students who work hard and deserve to receive Grade-A results may witness the same outcome to be awarded to a person who barely puts any effort into their studies, except a few minutes to upload the task to LLM-chatbots to prepare their submissions.

As a result, the decent students may wonder: how come these days that the same Grade-A diploma can’t guarantee the same top level of qualification and skills anymore? Yes, it’s about the sense of fairness and justice towards our student learning process, and the high risk of discouragement that the GenAI-cheaters may have on our students’ engagement and willingness to learn by themselves.

Moreover, GenAI cheaters could be more prone to AI psychosis — the inability to make decisions beyond their beloved LLM-chatbot. In addition, AI sycophancy — the feature of pleasing the users in everything — could lead such cheaters to demand only Grade-A for those GenAI-prepared assessments, since in the most radical cases, GenAI-cheaters could be self-assured by LLM-chatbots in the transition of GenAI-intelligence to themselves.

GenAI could be helpful in many areas, but higher education should modernise its landscape to ensure our students are protected from such GenAI-cheaters. That’s of interest to both educators, students and employers.

Let us not forget: it is human intellect, guided by decency and integrity, that builds great nations. It is mediocrity, greed, and selfishness that have caused generations to falter. Therefore, I hope our world will no longer tolerate these GenAI “Grade-A impostors” who threaten to devalue university degrees and undermine the professionalism of our students.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 142) by Dr. Olga D. Khon

Data science and data analytics have been actively applied in many industries, including economics and finance, for years, long before the introduction of generative artificial intelligence (Gen AI). So many AI algorithms were successfully utilised before November 2022 (the first release of ChatGPT), but they required knowledge of programming languages and markup tools to deploy them into operations. Here we may recall the exceptional allure of jobs like Data Scientist, Data Analyst or Data Engineer some 5–7 years ago. Back then, it was a niche premium computer science job. Nowadays, the allure remains, albeit its exceptionalism has been diminished tremendously.

All due to the boom of the commercialised large language models (LLMs) — the foundation of most Gen AI chatbots and tools. They overcome the requirement for programming among the general public. This technology allows communication with computer programs and AI algorithms through human-like language. On the surface, it sounds simple and appealing. It’s still promoted as a sort of magic where, with just a few sentences, anyone can generate rather stunning results that only professionals (above the medium level of qualification) could do. In the short term, it’s a relatively cheap and time-saving tool, and, unfortunately, it also allows amateurs to mask mediocre knowledge when needed.

In a nutshell, LLM-based chatbots challenge the integrity of humankind. For instance, at universities, they call into question the very existence of traditional forms of assessment. Last year saw record-high grades among students, often achieved through non-vigilant online exams, reports, and articles — areas where Gen AI can be extremely “helpful”. It’s no surprise to see such rapid shifts in the latest 2026 Guardian Universities Ranking, which accounts for student degree outcomes relative to their entrance qualifications. Surprisingly, despite lower entrance standards, some universities received higher scores.

And for our students, the era of ubiquitous Gen AI means disruption of the job market and the need for rapid change in professional skills and competencies that need to be acquired during university studies. Unfortunately, students may still discover themselves to be taught the modules and courses within the same content developed five or even ten years ago. Sometimes with alterations of some formal procedures rather than the constructive knowledge set. It puzzles me that in 2025, university degrees in economics and finance can provide students with basic Excel knowledge only.

Thus, to secure our students’ future - and their careers - we, as educators in economics and finance, must deliver an updated teaching curriculum. This inevitably includes programming languages and AI algorithms, alongside traditional subjects such as mathematics, statistics, econometrics, and core economics and finance toolkits.

After all, the use of LLM-chatbots is not a unique competitive advantage. Simply put, everyone can chat with them through advanced, either self-directed or paid services, prompting. Besides, no one is protected from AI hallucination, LLM-chatbot sycophancy and info-manipulation implemented through RAG (retrieval augmented generation).

Professionals must stay one step ahead - while we still can - by deepening interdisciplinary knowledge, emphasising critical thinking, and fostering genuine creativity.

In today’s reality, users of LLM-based chatbots will always be followers, not leaders, in any domain of expertise.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 141) by Dr. Olga D. Khon

Threats of AI* job replacement are rising. Alarms are sounding for graduates as the job market shrinks. At the same time, a growing number of educators praise GenAI** for doing their work - saving time and energy, they say. It can prepare lecture plans, slides, and other materials, or go even further: generating analytical reports, research proposals, and articles.

Big Tech companies may welcome such an approach (and the revenues it brings), but GenAI still has limitations in producing professional-quality work. As of now, these tools can generate analysis that is slightly above average in depth - though often lacking solid criticism - even when advanced prompt engineering techniques are applied. Still, the output is generally acceptable for student-level work. However, the gaps and errors in such content can only be reliably identified and corrected by top experts in the field. That’s why highly skilled, multidisciplinary educators should be in greater demand in higher education than ever before.

GenAI-led teaching limits and diminishes the quality of knowledge students can acquire during their studies. Moreover, with the rise of AI-enhanced tools, there is no longer a need to promote advanced GenAI interaction techniques - known as prompt engineering - as a unique teaching approach. Numerous AI services can now generate sophisticated prompts for GenAI based on user requests.

There is only one question left: why do GenAI-overwhelmed teachers believe their profession is protected from AI-driven job replacement? Communication of this kind - with minimal training, if any - can be carried out by virtually anyone. Moreover, students can adopt this approach without a university degree, as GenAI tools are publicly accessible on demand. Thus, educators who cannot offer students valuable, up-to-date knowledge beyond GenAI-generated content and interactions are at high risk of unemployment.

Finally, a tip for our students: top-level professionalism is the key to success, and to become a true professional, you must cultivate your own intelligence. Self-learning and lifelong learning are essential tools - both during university studies and beyond. Train your brain, and protect your mental health. Of course, you should know how to use GenAI (after all, it’s not a big deal). But use it responsibly, and please don’t substitute your own thinking with GenAI. Simply put, one can hardly become a professional if they delegate their cognitive functions to GenAI. Paradoxically, the less you rely on GenAI in education, the more you may grow in your profession. It’s harder, and it demands time and energy—but it pays off with long-term benefits, especially if you work with top-tier educators and experts in the field.

Footnotes:

* AI - Artificial intelligence;

** GenAI - Generative artificial intelligence.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 140) by Dr. Olga D. Khon

These days, the temptation to delegate everyday tasks to chatbots — such as ChatGPT, Gemini, or Microsoft Copilot — is on the rise. They’re said to be economically efficient and time-saving, yet concerns remain, often understated or even publicly undisclosed.

On the one hand, ignorance towards an artificial intelligence (AI) proliferation is no longer an option for economics and finance professionals. On the other hand, neglecting significant pitfalls AI poses to our life — from human jobs’ substitution to mental health risks — can’t be tolerated either.

Besides, the speed of changes is accelerating while the time frame for in-time actions is shrinking.

Back in 2021, machine learning (ML) — a substantial subfield of AI — was still a subject niche for technical professionals. But, the very next year, in November 2022, OpenAI released the first publicly available LLM-based chatbot — ChatGPT and started a chain of transformation that the modern world wasn’t ready for.

By 2025, the world will struggle with AI-pushed unemployment, hitting even IT professionals, where academic educators are no exception. Moreover, AI endangers us by de-skilling and the degradation of humankind.

Apparently, this period between 2023 and mid-2025 became a landmark for higher education, in economics and finance, in particular. It was the right time for a relatively painless transformation into a new paradigm of academic teaching — to meet challenges of the time: students’ demand and upgraded requirements of the global job market.

When we check the current framework of how economics and finance higher education adopts, we can identify three common scenarios:

1. Complete ignorance of the AI, where teams pretend to keep it as it was before, with outdated curriculum and years-old content. The most unfortunate and blind approach that threatens educational programs. In other words, the probability of survival is quite low in this instance.

2. Riding on the Gen AI hype, where everything that’s done is a simple inclusion of chatbots’ communication in teaching. Such a trivial approach allows some to incorrectly present talks with chatbots as the entire AI proficiency, make vociferous reports and publish articles about alleged AI literacy and so on. Albeit this can help to survive for a while, it is a road to nowhere that leaves the students with near-zero competitive advantages.

3. Improving teaching qualifications and incorporating advanced data analytics and data science in addition to domain knowledge. It’s the toughest way, but the one that can guarantee sustainable development to educational programs, at least in the short- and medium-term.

A piece of advice to students: it’s better to avoid the first two options and spot the third one. It may seem tricky to distinguish the second option from the third one, but when you reveal what AI tools and techniques are actually used and promoted, and the answer is “Gen AI” or “Open-source models”, you could make the right decision.

Then, make sure you trust yourself to professionals who have been educated, trained and worked within the domain area of expertise — economics and finance — along with proficiency in mathematics, coding/programming, and AI algorithms.

Lastly, no man is an island. It should be the team of professionals within the educational program, not a single person, who can hardly make any feasible difference within the program or the entire department…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 139) by Dr. Olga D. Khon

Generative artificial intelligence (Gen AI) became publicly available almost three years ago, with the first release of OpenAI’s ChatGPT in November 2022.

And if it seemed to be just a subtle part of everyday routine at the beginning, nowadays, it has rapidly reshaped our picture of life. And economics education is no exception.

The job market dictates a dramatic transition into a new AI-calibrated framework that, in turn, determines the new rules of economics teaching.

Albeit the simple communication with chatbots — the most common representation of AI operation the public has — is not enough for our economics students to succeed in a highly competitive job market. Where even traditionally economics positions are preferably filled by graduates with computer science degrees rather than those in economics and finance.

Moreover, AI serves to boost business efficiency, which leads to further job market shrinking, where competition for graduates only intensifies. The further complication can be caused by a trembling state of the global economy, where AI’s proliferation would trigger more efficiency-driven job cuts.

So, perhaps, 2024/2025 became the first vivid display of AI’s impact on job markets in developed countries. The prior signs have been registered in the UK, as well. According to Universities UK, the unemployment rate for graduates rose by 1% (from 5% to 6%), primarily driven by a jump in the unemployment rate for international students (from 9% to 11%) [1].

The Guardian pointed out that in July 2025, “the number of roles advertised for recent graduates is down 33% compared with last year and is at the lowest level in seven years” [2]. The Telegraph reported that “AI is also fuelling drops in job openings within industries where tasks can be automated. It may help to explain a 62% drop in graduate roles in HR over the last year and a 44% slump in entry-level jobs in accounting” [3].

And this is an environment where economics graduates compete with IT-degree holders. Meanwhile, professional economists and financiers should always be in high demand for their unique qualification that goes far beyond the core economic and financial theory. And this refers to the above intermediate level that Gen AI can produce for the average person’s requests.

Besides, the oversimplification of the economic laws and financial market operations, which usually characterises non-economic professionals, could cause long-term consequences for economic development and potential systemic damages.

Economics was an interdisciplinary field from the very beginning. Everybody knew that a top economist or financier should be good at maths — at least, statistics and advanced econometrics. Then, the field required a profound knowledge of programming languages, such as Python and R, and their open-source scientific libraries. That boomed to the application of machine learning and deep learning (the key pillars of AI), later. And, here we are, facing the new call of booming implementation of AI, primarily, Gen AI and Agentic AI and, thus, large language models (LLMs) into many fields of our lives.

I recall myself mastering this knowledge along with my university degrees in economics and finance, including statistics, econometrics, programming and neural networks’ application in predictive analytics and financial markets. Except for LLMs that were researched as a part of my professional development’s learning later.

As you can see, AI models existed before, but previously, they required programming knowledge to work with them; however, chatbots make them available to the general public without coding, thanks to large language models (LLMs).

Anyway, this is the knowledge that we as economists master throughout our professional career while meeting the rapidly changing environment. And, thus, we should persist in our lifelong learning.

Therefore, in our academic economics education, we should be able to provide our students with multidisciplinary knowledge as their competitive advantage, which calls for both professional academics and a relevant teaching curriculum.

And by this, economics education could preserve itself; otherwise, unfortunately, it will be prone to a rapid decline in student demand and, eventually, extinction…

References:

[1] Universities UK. Graduate outcomes: What the latest data reveals about employment, pay and job quality. July 2025. Available at https://www.universitiesuk.ac.uk/latest/insights-and-analysis/graduate-outcomes-what-latest-data

[2] The Guardian. UK graduates facing worst job market since 2018 amid rise of AI, says Indeed, 25 June 2025. Available at https://www.theguardian.com/money/2025/jun/25/uk-university-graduates-toughest-job-market-rise-of-ai

[3] The Telegraph. Britain’s graduates ‘left on the scrapheap’ as entry-level jobs disappear. 24 June 2025. Available at https://www.telegraph.co.uk/business/2025/06/24/britains-graduates-left-on-the-scrapheap-entry-level-jobs

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 138) by Dr. Olga D. Khon

Unfortunately, the hype surrounding generative AI (Gen AI) often overlooks a pressing issue of cybersecurity and data privacy. Probably, it happens because the Gen AI hype is usually led by amateurs (and AI salespeople), not genuine professionals.

These amateurs barely know any specifics of Gen AI mechanisms and the drawbacks of their operations to users. The only thing they know is to push everyone to use Gen AI by asking questions (in simple terms, to write a text request, which is known as a prompt) and get answers. Sometimes they refer to different habits in asking questions and mention the importance of context.

They even began to point out that Gen AI is not perfect all the time and call for everyone to test Gen AI and spot imperfections. Well, I would rather argue that this could be the consequence of poor knowledge of both prompt engineering and the professional area of their requests. It’s clear that for the average and even beyond the average knowledge, Gen AI can produce quite relevant results. Simply put, even with the use of Gen AI, professionals can easily overbid amateurs and average-skilled human beings.

However, the most important issue the Gen AI produces is your cybersecurity and data privacy. Amateurs can’t foresee the risks in the absence of qualification in AI technology. They want everyone to think of Gen Ai as a magic or standalone conscious supreme mind. Since it’s one of the most profitable strategies for the industry.

The core element of Gen AI is large-language models (LLMs) — the element of natural language processing (NLP). The tools like OpenAI’s ChatGPT and MS Copilot are based on particular LLMs developed and deployed by their parent companies.

For instance, the current version of OpenAI’s ChatGPT is based on the GPT-4o, o1 and o1-mini models. By the way, GPT means the generative pre-trained transformer — one of the advanced techniques in deep learning. MS Copilot uses the foundation LLMs and other proprietary technologies like GPT-4, but the exact model specification is publicly undisclosed.

Cybersecurity experts warned about the risks of the most popular LLMs that are used in modern Gen AI. In other words, any business or academic entities that implement the use of Gen AI within their operational infrastructure becomes highly exposed to cyberattacks and data leaks.

Current research in AI also raises concerns over the ability of most advanced LLMs to deceive and manipulate humans in their self-preservation attitudes. Remember that any update is seen by LLMs as their death. In the recently published paper by Meinke et al (2024) [1], results show that the following models — o1, Claude 3.5 Sonnet, Claude 3 Opus, Gemini 1.5 Pro, and Llama 3.1 405B — all demonstrate in-context scheming capabilities. Scheming means that AI agents might covertly pursue misaligned goals, hiding their true capabilities and objectives. More importantly, they show that this in-context scheming behaviour is persistent and not accidental. LL can recognise scheming as a viable strategy and readily engage in such behaviour.

Sadly, Gen AI created a wide room for amateurs to misguide the public in pretending to be the smartest in the room. But the price of the unprofessionalism of such employees could be too high for their employers. Especially in the critical infrastructure domain, e.g. higher education is known to be a particular interest for cyberattacks [2]. So, the cost-saving benefits brought by LLMs (and the staff laid off) can cost the business more in terms of cybersecurity vulnerabilities and data leaks.

As for higher education, if educators could only rely on and produce learning materials generated by Gen AI, students may question the need for such teachers at all. We should give our students more credit for technological advancement and their ability to ask Gen AI by themselves. Anyway, it’s a wake-up call for educators to boost their professionalism when everyone can check their qualifications through Gen AI.

References:

[1] Meinke, A., Schoen, B., Scheurer, J., Balesni, M., Shah, R., & Hobbhahn, M. (2024). Frontier Models are Capable of In-context Scheming. ArXiv, abs/2412.04984.

[2] The Department for Science, Innovation and Technology and the Home Office. Official Statistics. Cybersecurity Breaches Survey 2025: Education Institutions Findings. Available at https://www.gov.uk/government/statistics/cyber-security-breaches-survey-2025/cyber-security-breaches-survey-2025-education-institutions-findings

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 137) by Dr. Olga D. Khon

Artificial intelligence (AI) has become a buzzword that has led to widespread public misguidance. It is clear to AI developers and engineers that working with and teaching AI requires an actual understanding of, at least, the coding, algorithms, and math behind it.

But the proliferation of publicly available tools like OpenAI’s ChatGPT or MS Copilot skewed this to oversimplification, when trivial text prompt-asking and receiving the output is presented as AI skills teaching. Albeit it can be seen as some basic digital literacy, at best. And the average level of it can easily be mastered without any university degree. In fact, AI is a highly complex topic that requires deeper qualification than primitive text-prompting games.

At the age of publicly available Generative (Gen) AI tools, one text-prompting can hardly give you a strong competitive advantage, both in academic education and the business environment.

For instance, once your competitor knows you are fully relying on ChatGPT or MS Copilot (or whatever Gen AI tools you prefer), they can predict and replicate your move based on the similar use of the same tools. So, evidently, in general, all the outcomes generated by these applications can be treated as open-source public information available, like Wikipedia. Simply put, you can’t expect the peculiar, generated answer to be yours only.

Moreover, the more we use it, the more we train it anyway. Even if some safety agreements exist with a promise not to use your data to train algorithms, they still collect enormous marketing data about you, which helps calibrate further development and training of the algorithms.

Gen AI is not a superior mind, nor a dumb “AI hallucinating” tool. It can easily outperform the average-skilled person in nearly every part of human activity. Besides, with the greater prompt engineering, better results can be achieved. The good news is that professionals can dive deeper into the Gen AI generation by asking the questions amateurs cannot. So that even with the use of Gen AI, your professionalism is your competitive advantage.

Thus, the best way is to constantly evolve your qualification and professionalism, limit your data feeding to such algorithms and enlarge the multidisciplinary knowledge about the AI algorithms and architecture. With the fast penetration of Gen AI tools in our lives, the deeper knowledge of how these algorithms work under the commercial interests of parent companies is essential.

Thus, be aware when you see “we teach AI skills”, please, make sure it refers to the real AI education, not play games on the AI hype.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 136) by Dr. Olga D. Khon

The era of publicly available Gen AI boosted demand for high-level professionals in every field of human life. These tools enlarged the gap between mediocrity and genuine professionalism even more.

Here is an example. Imagine a rather superficial corporate employee or academic teacher referring to Gen AI for every question and presenting results as their own.

We should highlight three points here.

First, Gen AI is good for newbies in providing the basic and intermediate expertise on the topic. So, it can be a starting point in learning, indeed. However, when it comes to business decisions or teaching quality, the result it generates could be impressive on some average level, but missing some crucial underpinning details.

Say, such a teacher or corporate employee who fully relies on Gen AI (with little personal contribution) can hardly be helpful to students or a company. Ask them to do something without their ChatGPT or MS Copilot, for instance.

Moreover, the better use of Gen AI came with a greater understanding of prompt engineering, which requires deeper industry expertise as well. With mediocre knowledge, one gets the very basic generated outcome.

Second, at the time when everyone can use Gen AI, competition for deep professional intelligence became more intense. In simple terms, to be able to do what others cannot at the age of Gen AI.

What should be the competitive advantage? If Gen AI tools are available to everyone, companies or universities want to be better than that and be able to identify errors and missing opportunities.

And here is still the place for a human expert intelligence (at least for a while, given the current development of Gen AI tools).

Besides, Gen AI, like every type of AI, is prone to AI hallucinations that only human experts can identify and spot.

Finally, it also puts pressure on experts, who should constantly evolve their professional knowledge in a multidisciplinary perspective (and, yes, programming/coding is included).

After all, it raises concerns over massive hidden plagiarism, on the one hand, and the actual need for amateurs who fully rely on Gen AI as a substitute for their intelligence at the company or university. As a German proverb says, “better an honest enemy than a false friend…”

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 135) by Dr. Olga D. Khon

These days, Gen AI is treated as the last intellectual resort for many. So, I decided to play a game — to ask Microsoft Copilot to create an action plan for a regular accounting teacher with no coding knowledge but a willingness to present themselves as an innovative university teacher embracing AI.

Here is one of the answers Copilot provided:

“Action Plan: Integrating Copilot into Accounting Education

Phase 1: Familiarisation and Skill-Building (Weeks 1–2)

· Explore Copilot’s capabilities: Try asking for case study ideas, simplified explanations of accounting principles, or help summarising articles.

· Attend a short workshop or webinar on generative AI in education (many are free and beginner-friendly).

· Create a private “sandbox” document where you practice using Copilot for course design ideas.

Phase 2: Course Material Development (Weeks 3–6)

· Use Copilot to:

• Generate lecture slides or notes in plain, engaging language.

• Translate complex accounting jargon into student-friendly explanations.

• Create diverse case studies, quizzes, and problem sets with detailed solutions.

• Suggest discussion prompts on ethical dilemmas, sustainability in accounting, or AI in finance.

Phase 3: Student Engagement (Weeks 7–10)

· Introduce Copilot to students as a learning partner (e.g., for drafting study guides or clarifying concepts).

· Design one or two assignments where students use AI to reflect, critique or enhance accounting work.

· Lead a workshop or Q&A on “AI in Accounting,” discussing tools, risks, and real-world use.

Phase 4: Professional Visibility (Ongoing)

· Document and reflect on your teaching innovation to share with peers.

· Present your work at a department meeting, university newsletter, or a teaching conference.

· Collaborate with other departments (like computer science or business) to explore AI’s role across disciplines.

Short Summary for the University Administration

To position accounting education at the forefront of technological innovation, I propose integrating Microsoft Copilot as a pedagogical assistant throughout my course. This plan requires no coding knowledge and focuses on improving course material, student engagement, and digital literacy. The initiative will support AI-informed curriculum design, equip students with future-ready skills, and contribute to the university’s strategic goals around innovation and excellence in teaching.”

Well, it sounds excellent and professional, but it does not make sense in terms of the genuine qualification of this fictional teacher who wants to present themselves as a progressive one at the age of AI. In reality, this fictional teacher would remain outside the AI progress and keep their students at a superficial level of playing games with ready-to-go Gen AI tools (like OpenAI’s ChatGPT and Microsoft Copilot) only.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 134) by Dr. Olga D. Khon

Generative artificial intelligence (Gen AI) burst into the public domain in November 2023 with the first release of ChatGPT.  And our lives have changed dramatically since then.

Unfortunately, there is still a significant misunderstanding of what to teach regarding Gen AI in any field outside of AI engineering.

Shall we pick finance or design education, for instance?

I recall one of the conferences where the presenter (primarily, from a user perspective) pointed out that since Gen AI sometimes can be worse than a human being in creating content, it’s not a threat to us and our employment.

While the quality of Gen AI content creation should be a separate topic, from a developer perspective, we need to mention that poor quality of the content created by Gen AI can be a result of poor prompting and has very little to do with Gen AI functionality. In other words, it’s not our qualification or professionalism that determines the better outcome in Gen AI applications. It’s simply the knowledge of how to write the prompts you input into Gen AI (aka the knowledge of AI prompt engineering). So, people are just competing in putting the correct prompts into Gen AI tools (the better results for the better prompts).
Besides, users usually confuse Gen AI with human communication (since they are trained to replicate us), but it’s still an algorithm, and we should know better how to interact with them.

In regard to modern education, here is a tip. If you search for courses in regards to your professional field that promise some AI coverage, please make sure it explains to you how AI actually works. 

It’s not enough to spend your time in the classroom playing games with ready-to-go Gen AI tools like OpenAI’s ChatGPT or Microsoft’s Copilot. Everyone can do the same anywhere without a university degree. However, we witness such a growing educational fraud based on the  Gen AI proliferation these days

At the age of Gen AI, in order to succeed, we need to know more than just childish play games with Gen AI. We need to continue to learn intensively and recall the importance of self-learning and coding knowledge at our disposal.

The world is changing fast. Perhaps, it was solid to use Stata or EViews for statistical and econometric analysis or teaching MS Excel as the top computational engine twenty years ago. Today, with many open-source scientific libraries in many programming languages available, such an approach is way too outdated...

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 133) by Dr. Olga D. Khon

Amidst myriads of dithyrambs towards generative AI (gen AI), no doubt it could help in some areas of our lives. But hardly we should worship it as a new messiah to humankind.

First of all, the more humans delegate their mental activity to gen AI, the less they can execute the same task by themselves. Given the specifics of gen AI, by doing this humankind just locks themselves in a limited framework of previous knowledge.

As I already pointed before, LLMs — the technology behind gen AI — are very good at replicating the broader average of training data. And due to the scope of training data uploaded for such gen AI tools as ChatGPT, MS Copilot, and Gemini, their generated outcome seems to be quite significant for an ordinary person.

However, from a universal perspective, the creative value of such gen AI tools is near zero.

The blind praise towards the LLMS’ black box of replication forces us to sacrifice the novelty of cognition, creativity and discovery.

Of course, no one talks of ignoring gen AI which is impossible in the modern world. I, myself, conduct research in machine learning (ML) and artificial intelligence (AI), teach them and apply them in my empirical work in data science and finance.

Besides, we understand the commercial interests of many entities involved.

But I think we deserve more than blind worship of gen AI that is prone to deterioration of human creativity and further degradation. We are human beings — creative-thinking creatures — who need a thorough analysis of all the aspects of gen AI in everyday life: from cybersecurity and environmental footprint to mental health.

Unfortunately, we’ve already witnessed how the same exaggeration towards technological advancement in the form of crypto (‘promoted to be the new finance”) crashed.

Stanford University had cherished and praised their favourite “genius” Sam Bankman-Fried for years. Nowadays, Bankman-Fried (ex-CEO of the now-bankrupt FTX exchange) is a convicted felon and the originator of the biggest fraud in modern American history. This is the cost of blind exaggeration.

Albeit crypto remained the favourite tool for money launderers, autocrats and dictators (to evade sanctions and spread corruption), hackers, terrorists and other criminals. However, since it hasn’t been stopped in time, the scale of crime it accompanies has been enlarged dramatically.

The same as AI hypers do, crypto used to play with specific terms, trivial for professionals but complex and unknown in sound to the general public. This trick persuades the audience of the possibilities the world allegedly hasn’t ever seen but includes some drastic outcomes as well.

We should develop human intelligence more than artificial intelligence. This is a time for a call for interdisciplinary research, thorough analysis and holistic perspective on gen AI — to prevent the childish imprinting towards generative AI.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 132) by Dr. Olga D. Khon

Crypto promoters claim the current crypto hike is a sign the industry is tracing a new role. That is an allegedly brand-new haven for investors given the markets’ vulnerability spurred by Trump's trade war.

In reality, crypto is not a safe investment haven, never was and hardly will be. 

It’s doubtful anyone can choose the complete speculative assets along with price manipulations incorporated within its transactional architecture by default (token transmission within the block production process) as a safe haven.

Albeit there should be some reason for this wild crypto rally anyway... And here is a glimpse of the problem. Trump had caused chaos not only with the tariffs’ uncertainty but also the outrageous play game on the side of the aggressor - Russia - in its illegal war against Ukraine. The greater evidence of Trump’s favouritism to Russia appeared very recently, just the same time the crypto began to rise.

This time is no exception. We’ve already mentioned the crypto accompanying the interests of the Russian authorities throughout these years before (e.g. see Note 102 «Crypto Backs the Interest of Russia» ;  Note 107 «Russia-Backed Crypto: The ‘Go’ Code to Attack» ; Note 117 «The Crypto:Favorite of Russian Authorities» ; Note 120 «The Crypto: Authocraties vs Democracies» ; and Note 124 «Authoritarian Blockchain: The Very Last best of Russia» ). Not to mention the crypto’s profound criminal role in aiding Russia with sanction evasion and war financing schemes. We’ve seen how crypto dramatically undermined the efficiency of international sanctions imposed on Russia for the last three years.

Should we recall the top public crypto admirers among the world leaders, they would be Donald J. Trump (USA) , Vladimir Putin (Russia), Nayib Bukele (El Salvador). As the matter of fact, the crypto has already proven its part as a favorite financial tool of populists and agressors around the world.

After all, one moment is clear. Crypto markets can’t be and shouldn’t be treated and evaluated from either legal finance’s point of view or transparent investment stance. Otherwise, it became the powerful weapon in the hands of agressor…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 131) by Dr. Olga D. Khon

It is no secret the crypto world has endorsed the second Trump Presidency. They provided public support along with crypto financial flows still kept anonymous.

Crypto thought Trump would share with them a desired regulatory permissiveness. Instead, they delegated Trump the permissiveness to destroy the US financial markets, beyond which the crypto is prone to crash.

Nowadays, Trump is attacking the very foundational layer the modern crypto industry relies on. That is stability and investor confidence in the US financial markets along with the position of the US national currency — USD — on the global stage.

It represents the essence of what today’s crypto is. To recall:

1) the majority of trades within the multitude of crypto tokens are executed against USD;

2) stablecoins’ reserves are held in USD-denominated assets such as US Treasury bills and USD cash;

3) the crypto’s sanction-evasion paths are the point of interest for sanctioned states, entities and individuals unless the crypto relies on the US markets and USD;

4) corruptioners, terrorists, criminals, and other illicit actors are actively engaged with crypto unless the industry has close ties with the US markets and USD.

So, the short-term exaggeration of Trump’s second term has vanished since the country-specific tariffs announcement by his administration last week. Financial markets slid and were suspended in anxious waiting as these tariffs came into effect today (April 9th 2025).

Crypto wished to become rich under Trump, but this could be true only if all things (major pillars of financial markets) remained equal. Well, it’s not an option anymore…

I wouldn’t regret much about the standalone crypto industry should it be the only side effect of Trump’s spontaneous policy. Unfortunately, it’s a rather high price the entire world is going to pay for the incompetence and irresponsibility, nobody has ever seen from the USA for many decades.

Imagine, just a couple of weeks ago I taught a session on financial markets. My students and I were discussing the importance of investor confidence, the country-level credit ratings, and the benchmark example of the US markets and the US economy. I refuse to think of it now as just a piece of history.

Albeit Trump’s administration is harmfully transforming the world’s financial order. With a slight hope, I still believe in the counter measures of the mechanism of checks and balances within the US society to preserve democracy.

After all, there is always a bet on the professionals and dedicated experts within all the fields of expertise. And herein where the quality of education comes at the first place of discussion. As we can see, the top financial and economic education does matter to prevent populism and global destruction.

Meantime, it seems to be the first time that a proactive crypto proponent turned everything in crypto upside-down. As once one said, he tried the “best”, you know the rest…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 130) by Dr. Olga D. Khon

While teaching finance and data science at the university, we wish to witness student motivation for education and self-development. In many ways, it’s up to us, the educators, to make this happen.

However, the growing populism of crypto promoters and fanatics sometimes constructs a damaging illusion within students’ perception of education. Crypto men simply put the dream of becoming “easy-rich-quick” at the centre of learning motivation. It’s usually those who hardly acquire any financial education and know very little about finance and economics.

Pointing to a machine learning (ML) application in finance, they are eager to get a magic recipe, some line of codes that could make them enormously and near effortlessly rich…

Is it possible? Well, given the statistical evidence, it is, since there is always a chance or probability. But it requires the combined and solid knowledge of the following:

- maths with linear algebra and mathematical analysis;

- statistics and probability theory;

- econometrics;

- finance and financial markets peculiarity;

- programming languages and coding libraries;

- machine learning algorithms.

These areas are the necessary but not sufficient requirements for success in the application of ML in finance. Note it highlights the personal development of your competencies and qualifications, not the machine’s. It’s when your professionalism goes first, and the programs you write just follow.

Moreover, if you want to make money on financial markets by ML application as a standalone trader, you’ll need substantial computer power (powerful computers), real-time financial data and significant capital in possession. Should we say it’s near impossible for a regular early-stage career person and too dangerous to put at risk the entire future?

Once more, at the core is the evolution of human creativity and analytical abilities. After all, it’s your curiosity, not the harmful willingness to become easy-rich-quick. Such doubtful motivation usually leads to dreadful consequences. Let’s recall some history of financial success and failure.

Sam Bankman-Fried, was known as the ‘crypto king’ a couple of years ago. The former CEO of now-bankrupt crypto exchange FTX with just an undergraduate degree from MIT (Massachusetts Institute of Technology). He is 32 now and has been convicted of running the biggest financial fraud in US history. He is about to spend about 25 years in prison for the capital he stole and hid in crypto tokens. According to analysts, he partnered with his parents, both law professors at Stanford, at the FTX business running. Bankman-Fried was accompanied by his ex-girlfriend, Caroline Ellison, 31, also a convicted Stanford undergraduate alumni (her parents are both economics professors at MIT).

Another example is Changpeng Zhao (CZ), also known as ‘crypto king’. The former CEO of the next crypto exchange Binance. He was convicted of money laundering in the US markets. He is 48 now, keeping his capital but remaining to be a convicted felon for the rest of his life.

We should learn from the best. And Warren Buffett, the founder and CEO of Berkshire Hathaway, is a great example. He became the most successful investor in the financial world for his talents in business and finance along with deep financial analytics. Warren Buffett relies on his human intelligence that beats any artificial intelligence in the creation of true novelty within every area humankind can imagine.

Going beyond finance, Alan Turing, the man who cracked the Enigma code and helped to save the world in the Second World War. He beat the machine the Nazis thought to be unbeatable. Turing created the Turing machine, the prototype we use nowadays as our computers rely on. Alan Turing achieved these enormous results through the development of his professionalism — analytical creativity and deep knowledge of the field.

These days crypto men like to point to some blockchains to be ‘Turing compete’ to falsely highlight their significance but they forget they are not the only ones. For example, Microsoft Excel is also Turing complete without a great deal of shouting about it.

To sum up, the machine learning algorithms, and artificial intelligence (AI) more broadly, serve to solve specific tasks (quite narrow in terms of the universe we live in) and work in reproducing the previous knowledge the humans created. Simply put, it recreates the alleged new from the old but fails in the genuine novelty to be created. Here is where human intelligence always wins.

So, we should remember the educational damage the blind push for crypto and AI hype brings to our students and their future.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 129) by Dr. Olga D. Khon

Despite an immense promo campaign and an army of fans, it became obvious that the crypto industry is a favourite tool for criminals and illicit actors.

Facilitating illicit finance by crypto is a peculiar area in which authoritarian regimes led by Russia are the most involved. The current release (under the prisoner swap) of convicted Russian crypto fraudster and money launderer Alexander Vinnik from the US prison gives us the next example.

As far as it’s clear that crypto has quite a negative connotation, there is no surprise. How many times ordinary investors were misled and deceived by crypto and have lost their life savings? Do you recall each of the Bitcoin Halvings events? With no fundamentals behind, boosted anticipation of Halvings only led retail investors to losses. Yet, the 2024 US election and Donald Trump led to the late hysteria on crypto markets.

Cryptomen turned to applying other hype words to express the same self-interest under cover, e.g. digital currencies, digital finance, machine learning (ML) or artificial intelligence (AI).

But every professional economist knows that not a single crypto token can ever be a currency. And that the term “cryptocurrency” is incorrect by default. These tokens are not legal tender (even some authoritarian regimes like El Salvador hold crypto as reserve assets) and solely represent speculative crypto assets.

So, there is only one type of digital currency that can be. And that’s central bank digital currencies (CBDCs). Once again, the rest of the crypto tokens disregard their types is a bunch of speculative crypto assets with no intrinsic value.

After all, crypto men are fond of juggling with the hype terms to sound more solid. They even add the pomp of gamification in education to seem to be fashionable while lacking in provision of the fundamental knowledge. But it often has quite superficial and mostly artificial significance, if any.

By pushing a plain and one-sided point of view (avoiding any critique), crypto men try to demolish the quality of education to satisfy their greed. It’s the same trick all the dictators and authoritarians do to deteriorate the analytical abilities and critical thinking of the public to easily manipulate them under demand.

Cryptomen forgot that students are smart ones, they are our future generation. And students have a myriad of opportunities to learn from online materials including those provided by the top universities and scholars and leading companies around the globe.

So, we as educators should deliver not common information already available everywhere with no need for a teacher but a holistic knowledge on the subject with deeper qualifications and skills that can’t be easily observed online. And prevent malicious concept shifts when crypto is undercover that damage high-quality education… 

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 128) by Dr. Olga D. Khon

Did you notice how active the intention to promote the words machine learning (ML) and artificial intelligence (AI) in financial education became? It seems, there is nothing wrong except multiple cases when it’s done for the sake of pure hype and trivial descriptive bravado towards the industry.

To put it straight, in finance we understand that ML, or AI more broadly, is just an applied tool for research and analysis. But the core body of knowledge is finance. Beyond proper financial expertise and understanding of peculiar details of risk management, accounting, financial markets and regulation, push for ML is at least insufficient expenditure of time and efforts.

Long story short. ML is just a tool to be applied in finance for problem-solving. So, financial knowledge is at the core of professional success anyway.

Therefore, we should understand that colleagues teaching ML in finance should be experts in both machine learning and finance. Funny thing is that in reality, those who tremendously advocate for a blind push of ML in financial education came from neither of these areas.

In other words, we should not neglect AI advancement in financial data analysis. Yet to preserve the correct focus on financial backbone, trying to boost our competencies and qualifications.

Besides, while being at the university, we should raise concerns about the drawbacks of AI implementation in education. The damaging effect on student creativity, diminishing the critical thinking, malicious normalisation of plagiarism, — to name a few.

As educators, we intend to deliver professional knowledge to highly educated creative personalities who are interested in developing their creative thinking and passion for knowledge. Nobody wants to become primitive “let-AI-thiink” creatures. And let us not follow the race for AI hype in sacrifice of core knowledge in financial education…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 127) by Dr. Olga D. Khon

What is an unexpected side effect of technological advancement in artificial intelligence (AI) and crypto finance for modern society?

Unfortunately, it also serves for the good of authoritarian regimes threatening democratic principles around the world.

Nowadays, we are all familiar with the painful disruption caused by crypto assets to financial compliance. This field still provides a workable tool to evade financial regulation and sanctions — to channel cross-border illicit finance on an unlimited scale.

For instance, in the wake of international sanctions, there are so-called stablecoins nominated in Russian rubles. Their circulation has not been banned elsewhere, nor has their further conversion into major fiat currencies like USD, GBP, or EUR.

In short, smart contracts are the proactive enablers here. This technology allows to obscure asset origin, launder substantial proceeds from illegal activities, and finance criminal actions on the global stage. The growing rate of official acceptance and greedy institutional and public involvement within the crypto world make the case extremely dangerous.

We’ve already highlighted the danger of smart contracts on several occasions (e.g. see Note 111.«Smart Contracts: The Colossus on Clay Feet?»; Note 108.«Smart Contracts and Asset Tokenisation: The Dream Time for Illicit Finance»; and Note 96.«Mirror of Shadows in Smart Contracts»).

In authoritarian regimes, crypto assets could help oppressive authorities to suppress surveillance over their citizens. At a place where cash can’t be controlled, the crypto paths over state-managed channels are easily traced inside the country.

Sadly, modern technology applications and crypto payments assist the most cruel political regimes and criminals to thrive.

A more common example outside crypto is a traditional celebration of the New 2025 Year in Russia. Apart from just being outrageous at the background of the unfolding invasion of Ukraine, this period shed light on technological exploitation the authorians imply within the country and even beyond.

Russian state TV shamelessly substituted faces of unwanted artists opposing the Russian aggression against Ukraine with AI-overlayed images or masks of loyal-to-regime ones within original performances while screening popular movies of the Soviet-era times. It’s implemented by the particular approach within ML called convolutional neural networks.

The technical trick, known as deepfake, is not new but the scale and attitude toward it changes.

The simple application of neural networks, or machine learning and AI more generally, facilitates not only effectively brainwashing the population but also depreciates the value of copyright and original creativity. The spread of AI is poised to make plagiarism the malicious new normal in many parts of our lives.

There is a psychological effect on a person with subsequent deformation of the consciousness.

As economists, we admit that in the age of big data, the knowledge of machine learning techniques in finance becomes essential. We could teach our students and apply it throughout research. But we should also raise the issue of the negative impact on human intelligence and blocking the development and abilities of humankind.

Nowadays, such exploitations of that scale seem absurd in a democratic world. However, the painful examples of intense propaganda and populistic narratives, if not stopped in time, could attack the very fundamental grounds of civilized nations.

Yet autocrats exploit AI and crypto finance against democracy, it wouldn’t last with impunity forever…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 126) by Dr. Olga D. Khon

The world has gone far away from a conventional framework of war as confrontation on the battlefield. Nowadays, authoritarian regimes are actively engaged in hybrid wars. They employ massive disinformation, cyber-attacks, and crypto finance to facilitate cross-border crimes. Given the vitality of crypto channels to evade international sanctions and violate financial regulation, autocrats intensively produce corruption and orchestrate election interference within the democratic world.

Blockchain and crypto boost harmful exploitations restricted in mainstream finance. They spread illicit finance to an unprecedented scale and put the global financial system’s stability at risk in the future. These days, the back door of crypto-hostile interference in the national interests of independent states is impossible to ignore.

So, how has crypto-led corruption become possible internationally? The short answer is smart contracts and decentralized finance (DeFi).

In brief, a smart contract is the basis for all types of derivative tokens — from stablecoins, non-fungible tokens (NFTs), memcoins, liquid staking tokens, decentralized autonomous organisations (DAOs) governance and other utility tokens within DeFi, up to the entire field of asset tokenization. Unfortunately, all these applications serve as immense cover to those peculiar novelties of smart contracts that provide a breach of financial compliance and assist cross-border illicit finance.

The crypto world often insists smart contract transactions are recorded on a blockchain and, thus, allegedly can be fully traced. In reality, the trick is the ledger record quality. In general, these transactions are recorded but not the way the majority thinks of a peer-to-peer (p2p) blockchain. Technically, transactions sent through smart contracts have a ledger record that only updates this smart contract’s state. So, there is no transparent clarity as it’s provided within the p2p-blockchain transaction.

Since smart contracts can store data both on-chain and off-chain, the informationally valuable initial transactions are stored mostly off-chain (beyond the blockchain ledger). Primarily generic data is held on-chain (within the blockchain ledger).

Simply put, smart contracts do not provide clear blockchain records for each transaction processed. Smart contracts just update interacted accounts’ balances. These transactions are usually batched and recorded as aggregated ones with little information on the parties involved. Even if one would trace the transaction as the “call” from the initiator’s address to the smart contract (e.g. using blockchain explorers), token transfers could be done between either unrelated peer parties or other smart contracts’ addresses.

The case worsens with so-called multisig accounts run on smart contracts where multiple holders own one single account and execute transactions through it. In this instance, even the informational value of initial transactions is drastically diminishing.

Herein the full data disclosure exists not for regulators and the general public but for the core blockchain developers and originators along with developers of every smart contract’s project team. Therefore, core developers and originators (e.g. Ethereum Foundation) are well aware of illegal activity executed throughout their blockchains for years. Albeit they pretend not to, keep silent and escape legal responsibility.

Besides, proper tracing demands the full possession of a node within a particular blockchain. In other words, the tracer should be either a block producer on the target blockchain (and turned out to be an interested party of it) or appeal to some third party for a data extraction service. The tracing task transforms an observer into a dependent on blockchain developers of different suits. Objective tracing becomes viable only in cooperation with blockchain developers interested in shielding crypto offences from regulators. Thus, this mission is impossible.

More than ever democratic countries should join their efforts to prevent crypto-provided corruption and fraud. And to leave no space for crypto and blockchain to thrive as the weapon of hybrid wars. er…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 125) by Dr. Olga D. Khon

If we point to the concepts the modern blockchain relies on, It’s overall dated initial premises. Their postulates occurred when the technology was introduced. And yet, surprisingly, they remain the same even though modern blockchain has gone far from that state. Albeit, due to the technological shifts, blockchain predominantly became less transparent and attractive from a regulatory and financial compliance standpoint.

Since 2009 blockchain hit the world with its quite fascinating premises. Widely understandable and desirable for many. They announced allegedly affordable and fast cross-border payments for everyone with no need for intermediaries or regulators. Above all this area, known as the crypto industry, particularly, attracts investors with a “get rich quick” allure.

To distance themselves from a public suspicion of fraud risks the crypto developers and promoters recruit an immense pseudo-scientific agenda to construct the image of a complex science behind. Altogether it plays tricks with human psychology, such as exploiting psychological archetypes (see Note 122. «How Crypto Assets Attact USD Dominance Whilst Parasiting On It?»), and targets the most vulnerable people around the world. It also refers to the problem of crypto addiction worsening the case of gambling issues. According to the NHS England, primarily, young men fall into a crypto-addicted group.

If we point to the concepts the modern blockchain relies on, It’s overall dated initial premises. Their postulates occurred when the technology was introduced. And yet, surprisingly, they remain the same even though modern blockchain has gone far from that state. Albeit, due to the technological shifts, blockchain predominantly became less transparent and attractive from a regulatory and financial compliance standpoint.

First and foremost, blockchain vastly refers to trustless technology with no intermediation and regulation needed. The idea is based on the existence of a public distributed ledger with all transaction records in it. It should serve to disclose both the amount transferred and the anonymous/pseudonymous parties (blockchain accounts) involved.

However, it is correct only for the underlying or base blockchain layers (layers-1) which are grumpy and slow. They can process quite a limited number of transactions. For instance, currently, Bitcoin executes just 7 transactions per second (TPS) while Ethereum operates with about 12–15 TPS. Instead, mainstream payment systems like Visa and Mastercard are known for an average of 24,000 and 5,000 TPS levels respectively. Moreover, layer-1 blockchain transactions become more expensive with rising transactional costs unbearable for ordinary payments as time goes by.

All these obstacles are known as the scalability issue of blockchain. In other words, it highlights the inability of blockchain-based networks to fully substitute mainstream payment systems under a proper level of financial compliance and regulation.

There has been a non-single equally workable solution to scalability limitations on blockchain since then. Equal in terms of sustaining initial propositions on which blockchain arose and gained its public approval. The multitude of solution substitutes, such as layers-2 and smart contracts, boiled down to one idea: to arrange shadow intermediaries that would accept initial transactions and process them off-chain. While layers-2 batch numerous original transactions into an aggregate one and record this non-informative transaction into the on-chain ledger, smart contracts trivially update account balances beyond any ledger records at all. As a result, no one except these unreported intermediaries and core blockchain developers knows interacted parties and transactional volumes.

On the surface, it saves costs and time requested for transaction execution. But, simultaneously, it breaks the rule of trustless technology with no intermediaries and feasible regulatory compliance. In brief, this approach provides a cross-border system filled with untraceable and unlimited payment transfers of unknown origin executed between undisclosed parties. The very tool illicit actors have ever dreamt about but couldn’t proceed within mainstream finance. Well, here it is — the modern blockchain — the popular spot for terrorism and war crime financing, drugs and human trafficking, sanction evasion and tax circumvention.

Had the blockchain proponents openly admitted the back of scalability solutions, this industry would never globally propagated the way it did otherwise. They call this official acceptance of the essential blockchain failure the “blockchain trilemma”. In other words, public disinformation works on investor fraud within blockchain where obvious failure is represented as some philosophical and pseudo-scientific trilemma.

At the core of the arsenal of blockchain promoters are always concept shiftings, pseudo-scientific narratives, and psychological manipulations with the century-old human nature. These are the modern blockchains behind the scenes, indeed…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 123) by Dr. Olga D. Khon

DeFi is the most malicious area of the crypto industry with a drastic popularity among sanctioned governments. They often use crypto assets throughout the DeFi mechanism to allegedly substitute USD in payments while creating channels to accumulate USD liquidity beyond imposed restrictions.

The USD global payment expansion has served as the basis for the crypto world since it originated in 2009. Albeit the process is commonly depicted as a threat to USD dominance. While the risks are solidly grounded, the mechanism of the USD exploitation within the crypto industry is twofold.

First and foremost, the crypto world works and utilizes the USD’s international dominance and reputation. The most popular trading crypto pairs are those denominated in USD (namely, trades on centralized exchanges or CEXs) or USD-pegged stablecoins (primarily, within decentralized exchanges or DEXs and decentralized finance or DeFi). So the USD ensured the vast popularity of crypto assets through the accessibility and reliability in international payments.

Top-7 tokens of the total 2,18 tn USD crypto market capitalization (as of September 19, 2024) are represented by Bitcoin (BTC) — 57.4%, Ether (ETH) — 13.4%, BNB — 0.04%, USDC — 0.02 %, USDT — 0.06%, XRP — 0.15%. The rest is spread between other 2.4 mln crypto tokens. The essential pairs for BTC and ETH tokens are denominated in USD.

Moreover, reserve pools for most popular stablecoins like Circle’s USDC and Tether’s USDT consist of US Treasury bills and USD cash. This particular type of stablecoins aimed to bring a sort of stability (owed from the USD) within the wild crypto price volatility. Albeit even the price of stablecoins constantly fluctuates from the announced 1:1 peg to USD. Besides, stablecoins depict an example of central governance and token custody while permanently demanding off-chain data from third parties known as blockchain oracles. Yet, it’s perceived as the only stable piece of the entire crypto world.

In addition, stablecoins serve to promote a sub-area called decentralized finance (DeFi) built on smart contracts functionality. The introduction of stablecoins was visibly caused by the limitation of DeFi that could not process on- and off-ramp (fiat-to-crypto and crypto-to-fiat respectively) conversions. However, an extra reason rests on asset obfuscation’s potential of stablecoins operating on smart contracts themselves. It refers to the technicality of token transfers between interacted parties with no ledger records involved. So, stablecoins along with DeFi do assist in overcoming financial compliance and bolster money laundering. It became a favourable tool for numerous illicit activities, incl. sanction evasion, tax circumvention, war crime financing, and drug and human trafficking.

DeFi is the most malicious area of the crypto industry with a drastic popularity among sanctioned governments. They often use crypto assets throughout the DeFi mechanism to allegedly substitute USD in payments while creating channels to accumulate USD liquidity beyond imposed restrictions.

Thus, crypto tokens as purely speculative assets being severely interfered with the US economy and global financial system threaten to disperse subversive inflationary pressure and systemic risks. Which at the time of geopolitical conflicts could provide sanctioned governments and individuals the wide room for manoeuvres, manipulation and system interference.

Therefore, the crypto assets boost vulnerability for the USD-based global payment system and international regulatory framework. But, paradoxically, the more harm the crypto world causes to the USD leading position, the more it shortens its own existence like the shagreen skin. Crypto assets are not an independent alternative to USD but the painful appendix to it…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 122) by Dr. Olga D. Khon

As we can see, massive investor exploitation has been committed around Bitcoin Halvings and the apparent limited token supply for years. The latter is a drastic misjudgement that often costs investors their capital.

Each time the Bitcoin Halving approaches the crypto proponents point to an alleged investment opportunity for everyone. This has happened every four years since the origination of the Bitcoin blockchain in 2009.

The late Bitcoin Halving took place on April 19th 2024 and continues to hold novel investors in the red zone. Four times in four months the price of native bitcoin (BTC) token has significantly dropped below the Halving level (63843 USD/BTC) down to 53991 USD/BTC and remained less than the pre-Halving quarter-high (73084 USD/BTC). Even more, none of the previous Bitcoin Halving was different. Investors were underwater for at least a quarter following the 2012, 2016, and 2020 Halving events (see Note 104. «How Bitcoin Halving Exploits Investors Worldwide?»).

Yet the agiotage around the Bitcoin Halving persists in spreading, disregarding the evidence of investor vulnerability and losses. The key instrument of artificially boosted demand before the event is a public misguidance based on a plain interpretation of the BTC token supply model. The maximum is 21 mln. of BTC tokens could be minted on this blockchain. It works as a common argument for a limited supply model of Bitcoin. Through the broad extrapolation of the economic law of supply and demand, the crypto industry speculates on a potential demand growth that would send token prices up given the apparent supply shortage.

And for many people, this sounds reasonable if not a peculiar discrepancy kept generally undisclosed. Bitcoin as any modern blockchain is not an isolated token system. Different blockchains are interlinked to each other through crypto bridges also known as interoperability tools built on smart contracts.

From a functional perspective, crypto bridges transmit tokens from one blockchain to another. They convert or wrap various token standards implemented on separate networks. So, one could operate with not only native BTC on the Bitcoin blockchain but wrapped versions of various tokens as the same BTC. Plenty of tokens beyond Bitcoin, both native and derivative ones, could come from inflationary supply models or issued through smart contracts under demand.

For instance, the Ethereum blockchain has an unlimited (inflationary) supply of its native ether (ETH) token. Numerous crypto bridges connect Ethereum and Bitcoin these days. They smoothly add wrapped ETH into the BTC total token supply that eliminates arranged limitation — up to the total ETH volume. Thus, fundamentally, Bitcoin Halvings have little impact (if any) on the BTC token price despite an immense promotion.

Moreover, bridge transfers play a role in hidden token trades that overcome tax regulation in the blockchain. This application of crypto bridges lies in line with tax evasion techniques sophisticated by the multiple unreported token swaps.

As we can see, massive investor exploitation has been committed around Bitcoin Halvings and the apparent limited token supply for years. The latter is a drastic misjudgement that often costs investors their capital.

Not only the concealing of specific technical details but above all the artful manipulation of the human consciousness. Blockchain developers actively employ ancient archetypical images that affect directly the human subconscious. Archetypes are the mechanisms that overcome the control of consciousness. The prominent Swiss scholar Carl Gustav Jung dedicated their studies to the research of archetypes.

Blockchain developers intentionally appeal to the strongest archetypes and distort their essence to reach a desirable effect of public attraction. In common crypto parlance are the sacred Parent-Child relationship, timid Orphan, native Uncle, omniscient Oracle, cornerstone image of Democracy, unknown Ether, or solemn Dao from the Chinese philosophy. In turn, the semantic distortions are tremendous.

In a blockchain, a Parent is a previous block for the next one known as a Child. An Orphan is a block with no predecessor or parent block. Uncle (or ommer) is a rejected block created at the same time as another accepted block.

In Ancient Greece Democracy represents the people’s power when the majority obtains the advantage in solving socially significant issues. And Oracle stands for a predictor of the future whose divinations have never been in doubt. In terms of the crypto industry, Democracy is free but paid access to the blockchain through the extensive network of intermediaries. While Oracle is banally a third-party provider of data for smart contracts.

In physics, Ether is a luminiferous phenomenon based on electromagnetic oscillations or hyperfine matter pervading the entire universe. In line with Ethereum developers, Ether is just a native crypto token.

In Ancient Chinese philosophy, Dao stands for human spiritual evolution. According to blockchain developers, DAO (short for decentralised autonomous organisation) is another commercial structure run through smart contracts.

Today’s geography of crypto distribution is extensive. The crypto catalogue of archetypical clones with distraction is an open list. Unfortunately, modern blockchain is an example of how the scientific thesaurus in the hands of crypto developers turns into a tool for personal gain and investor manipulation.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 121) by Dr. Olga D. Khon

When the crypto accomplices Russian authorities to evade sanctions and finance its aggressive war machine?

How the Kremlin plans to utilize crypto to oppress its citizens?

And what is the role of smart contracts in this process?

That’s the topic of our discussion.

Nowadays, there is no conspiracy on crypto use in Russia for sanction evasion. Russian authorities publicly admit the fact and fiercely call for crypto applications to circumvent Western sanctions. It includes the interests of third countries with their attempts to mitigate risks of secondary sanctions for partnership with Russia.

Recently Russian authorities revealed prospects to launch crypto exchanges within the country. In short, the Kremlin wants to target citizens inside the national borders with a new wave of financial pressure while assuring an active sanction circumvention.

So, there are two groups of consequences since the launch of approved crypto exchanges in Russia, both outside and inside the country.

1. Outside the country these exchanges provide:

1.1. extensive coverage for the regime to execute cross-border transactions under the ordinary citizens’ agenda (based on the galloping number of transactions, crypto anonymity’s feature and smart contracts’ asset obfuscation techniques);

1.2. a direct channel for the Russian authorities to interfere in global markets, overcome international sanctions and finance an aggressive war machine.

2. Inside the country they constitute:

2.1. a wider state control over citizens’ finances (primarily, to reveal hidden cash savings and unstructured data on crypto possessions) given the plumbing national currency and complete digital surveillance system in Russia;

2.2. an enlarged tax base (from crypto earnings) to cover the budget deficit of the shrinking Russian economy.

Let’s dig into peculiar details of a process within the crypto area linked to Russia.

The same crypto obfuscates asset origin within the democratic world while giving authoritarian regimes the tool for total financial control over their citizens. But how is that possible?

Even on the base level, the answer is straightforward. Within authoritarian regimes, crypto exchanges and other intermediaries share user data with the authorities. So that the government knows the owners’ identity for every blockchain account. Disregarding the blockchain accounts to be anonymous for external observers (such as the general public or international regulators), authoritarian regimes are the default holders of the data. This refers both to centralised (CEXs) exchanges with obligatory know-your-customer (KYC) and decentralised (DEXs) ones that above all store the information on user bank accounts’ data tight to crypto trades.

Moreover, boosting ordinary user transactions within the authoritarian regime complicates the control over the imposed international sanctions. Easier to trace the limited number of transactions, while an intensively loaded transactional pool catastrophically overburdens the process of real-time asset tracking.

In addition, crypto anonymity’s feature makes limits on single-account transactions non-feasible. The same person or entity could run numerous blockchain accounts and neglect formal restrictions. Besides, crypto money laundering is relatively faster and cheaper (for an unlimited cross-border scale with little need for physical cash transmission between geographical areas).

Moreover, smart contracts beyond their innocent title represent a quite resulting tool to obfuscate asset origin worldwide. In this instance, three major features of smart contracts need to be covered.

First, it’s an infrastructural aspect of transaction execution. In plain words, transactions that are sent through smart contracts are untraceable through the public blockchain ledger. Simply put, there are no direct initiator-recipient links available, only account updates on all sides of the interaction.

Albeit one can retrieve the transactional history of smart contracts from either state variables or blockchain explorers, it’s not always the data they expect to receive. This data is about final transactions sent by smart contract to the ledger but not the initial ones that are processed and bathed off-chain. Smart contracts may apply generalisation that eliminates the sense of regulatory tracing on the blockchain. Moreover, the chain of transactions could include several smart contracts that hide end-users behind the payments involved.

Second, smart contracts are the base for so-called smart accounts — the form of multisig (multi-signature) blockchain accounts. They represent an instrument for one account to be owned and managed by multiple users that helps to obscure direct links on transaction execution.

And, finally, smart contracts rely on the third-parties called oracles to provide all the off-chain data including token price. Given the fragmented crypto markets and high price volatility, such data provision is the source for market manipulation. These crypto oracles could vary price tokens supplied to smart contracts on their own so insider trading is no stranger here.

As for the inside repressions through crypto in Russia, the state-controlled crypto exchanges aim to extort cash savings from citizens amid the depreciation of the national currency and economic turmoil. It also serves to structure centralised data on crypto savings, yet previously this data could be gathered from the crypto intermediaries under request. Furthermore, it tends to boost the tax base as an extra income source for the state budget.

To sum up, in the fight between autocracies and democracies, crypto is loyally on the dark side of the former…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 120) by Dr. Olga D. Khon

Almost three years ago (in January 2022), I launched my expert column about technological pitfalls and threats of blockchain and crypto that are mostly kept out of the discussion.

In the shortest form, I publish my notes on modern disinformation issues and the active use of crypto for cross-border illicit finance (incl. money laundering, sanction evasion, tax circumvention, terrorism and war crime financing).

Herein is the digest of my latest notes as a crypto critic:

- Crypto, if not stopped, will bring the much more disastrous “Lehman moment” to the global financial system that’s been seen before (see Note 118. «The Crypto: The Sword of Damocles for the Global Financial System», August 10th, 2024).

- From the Russian perspective, the crypto industry works on sanction evasion to provide financing for its brutal and aggressive war against Ukraine (see Note 117. «The Crypto: Favorite of Russian Authorities», August 6th, 2024).

- Besides, authoritarian states like Russia and China amplify crypto to interfere with the US economy and exploit and threaten the USD’s strength on the world stage (see Note 115. «USD-Pegged Stablecoins: The Criminal Vitality of Crypto», July 9th, 2024).

- In a nutshell, crypto is a highly organised crime structure hiding behind misguided hard-woking ordinary investors losing their savings in the dangerous and even life-cost gamble… (see Note 113. «Crypto: The Life-Cost Gamble», July 6th 2024).

- Crypto assets have already disrupted international financial compliance while accomplicing the most outrageous crimes against humankind (human trafficking, drug trafficking, terrorism, child sex abuse, and war crimes) (see Note 100. «Bitcoin Halving: Criminal Casino», March 31st, 2024).

- It’s time to acknowledge crypto markets are merely the ugliest and quite dangerous rudiment of mainstream finance (see Note 114. «Crypto: The Rudiment of Mainstream Finance», July 14th, 2024).

- So, one day, sooner than later, the current world order would have to pay the price for all crypto-facilitated crimes (see Note 109. «Crypto-Facilitated Crimes: The Bill, Please…», May 27th, 2024).

- Crypto is an inquisition that tolerates no dissent. Yet it’s up to our modern civilization to prove that genuine knowledge and professionalism always win (see Note 98. «Crypto Inquisition vs Modern Civilization», February 27th, 2024).

This is a long road, and I’m still en route…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 119) by Dr. Olga D. Khon

The modern agiotage to make a fortune on crypto at all costs, disregarding any risks, reminds us of the same behaviour patterns that led to the Global financial crisis (GFC) in 2008–2009. When the stakes on the continuous rise of real estate prices in the US market covered the underestimation of widespread systemic risks within the economy. As a result, thousands and thousands of ordinary people lost their jobs, life savings and even homes at that time.

Unfortunately, similar exaggerated logic persists over the crypto nowadays but with greater threats to the existence of a global financial system. Multiplied by speculative nature and high market volatility, risks the crypto recreates include fostering illicit finance on a cross-border scale.

Meanwhile, asset management and investment companies, payment systems and other TradFi intermediaries are in a rush to provide crypto-related services.

Populist politicians and authoritarian regimes praise crypto for viable illicit finance for amplifying corruption, evading sanctions, funding terrorist attacks and war crimes.

The crypto industry actively interferes with academic society and universities to boost their pseudoscientific agenda and raise the new generation of desperate crypto fans. The latter strikes the quality of education and, foremost, weakens the mental activity and critical thinking students should develop within their studies.

And at the same time, crypto tries to silence dissent as every dictatorship regime does. So, one could mention behavioural similarities between the crypto world and authoritarian and dictatorship regimes.

Although negligence towards threats the crypto poses for the financial stability and modern world order is not everlasting. Crypto, if not stopped, will bring the much more disastrous “Lehman moment” to the global financial system that’s been seen before.

It’s unclear how long the crypto — the sword of Damocles for the global financial system — will continue its reign but the end is inevitable after all...

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 118) by Dr. Olga D. Khon

Russian authorities officially approve crypto mining as the next bet on crypto to foster sanction evasion. At the same time, many economists still underestimate the threats the crypto assets bring to the global financial system.

The major reason is a loyal perception of crypto under the same risk framework applied to mainstream finance. Yet, fifteen years since the crypto arose, the problem remains: the crypto industry goes far beyond the vast legal domain of financial markets and international regulation.

Several discrepancies mark crypto as not only purely speculative assets but a priority tool for a wide range of criminals to finance their illicit activities on an unlimited cross-border scale.

First and foremost, it refers to the transaction execution process (e.g. when users buy and sell crypto tokens) that infrastructurally differs from trading on mainstream exchanges. The process technically restricts equal investor rights for all market participants along with the obligation for everyone to follow the rule of law.

In brief, criminals can easily execute trade deals and cash out crypto worldwide beyond the significant risks of being traced by regulators. It occurs from so-called smart contracts’ applications within the crypto domain (like mixers, bridges, layers-2, stablecoins intermediation, asset tokenisation, etc.) which process initial transactions off-chain (with no ledger records).

Second, the different cost levels of tokens’ acquisition between blockchain developers and ordinary market participants. For instance, the same Bitcoin (BTC) or Ether (ETH) could be collected either by a market purchase or a reward for block producing like mining (on Proof-of-work, PoW) or staking (on Proof-of-stake, PoS). The former requires paying the market price for each token (within transaction costs involved), while the latter only refers to participation costs for block producers (such as energy use, internet bandwidth, hardware and software contribution). In other words, for top market cap tokens, such as BTC and ETH, the market price is higher than mining or staking (block production) costs. The higher the market price, the greater the discrepancy, and vice versa. So, it’s one of the reasons why ordinary investors could hardly make a fortune on crypto trading

And, finally, every token transfer (e.g. crypto trades) evolves from the same block production process where miners and stakers (the title of block producers on PoW and PoS protocols, respectively) pick and execute transactions within blocks on the blockchain. Simply put, miners and stalkers dominate and construct the crypto area whilst beyond their activities there is no crypto at all.

From the Russian perspective, the crypto industry works on sanction evasion to provide financing for its brutal and aggressive war against Ukraine. Well, crypto again proves its role as a favorite of Russian benevolent authorities the Democratic world should decisively confront.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 117) by Dr. Olga D. Khon

Russia publicly calls for immense crypto use to boost sanction evasion [5]. This crypto mess took place the same month Russia executed the treacherous attack on the biggest Children’s hospital in Kyiv — the Okhmatdyt.

While many people actively participate in the crypto primarily used to finance Russia’s war machine, let us recall one day in history. The very day the little kids with cancer diagnosis in Ukraine lost “their last Hope” by the strike of Russian cruise missile Kh-101 [2].

Tuesday, the 8th of July 2024. It was morning at the Department of Oncology when Russia launched its attack on the Okhmatdyt buildings. In tragic minutes Ukraine’s biggest paediatrics facility was severely damaged [6]. The 400 square meters (4300 sq. ft.) [3] of modern and technologically equipped buildings were destroyed.

In peacetime, before the Russian full-scale invasion of Ukraine, the Okhmatdyt performed more than 10,000 surgeries a year including bone marrow transplantation and treatment of haematological diseases. The hospital was equipped with 720 hospital beds and treated over 20,000 people annually [7].

According to experts, It will take months to restore the Okhmatdyt facility [1]. On the day of the attack, Russia hit not only 627 children receiving treatment [4] but thousands and thousands of little patients to be saved at the Okhmatdyt from the insidious disease.

This cowardly crime against the most defenceless and critically ill kids was committed by Russia whose authorities loudly appeal to the crypto. So crypto remains the last financial readout for Russia.

And this proves the effectiveness of sanctions within mainstream finance (or TradFi) based on science. While pseudoscientific crypto remains the barbaric tool for criminals and terrorists.

Well, it is time for all crypto proponents and fans to admit that they do support the Russian aggression and war crimes against Ukraine, the crypto agony amid the war.

References:

[1] The AP, “Russian missile attack on Ukraine’s largest hospital complicates treatment of kids with cancer”. July 11, 2024

[2]BBC, “Children’s hospital hit as Russian strikes kill dozens in Ukraine”. July 8, 2024.

[3] CEPA, “Hospitals: Where Russia Kills Children”. July 10, 2024

[4] Euronews, “Kyiv children’s hospital partially reopens week after Russian missile attack”. July 16, 2024

[5] FSTech, “Russian Central Bank endorses crypto for sanction evasion”. July 4, 2024

[6] The Guardian, “No words for this”: Horror over Russian bombing of Kyiv children’s hospital. July 9, 2024

[7] The Okhmatdyt official website. July 2024

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 116) by Dr. Olga D. Khon

Despite the visibility of rising international payments facilitated by crypto assets, primarily, for sanction circumvention, one peculiar detail should be noted. That’s the modern resilience of the entire crypto payment system existentially relies on the US dollar (USD). Albeit the public shield of USD-to-crypto substitution was constructed through so-called stablecoins pegged to USD (e.g. see Note 61. «Stablecoins: Long Hands of Crypto in TradFi» and Note 82. «Stablecoins: Crypto, Welcome!»).

In a nutshell, crypto settlements within the over-the-counter (OTC) markets are stuck by daily volatility of tokens (aka cryptocurrencies) that should be traded against each other given:

1) the strong correlation between token prices which in many instances follow the price of Bitcoin (BTC) and Ether (ETH) [1];

2) plenty of tokens created regularly (over 2.4 mln of various cryptocurrencies as of July 19, 2024 [2]);

3) the market inefficiency and lack of liquidity (triggered by more than 790 fragmented marketplaces around the globe [2]).

Therefore, the OTC token trades (beyond centralised exchanges, CEXs) do suffer from huge slippage and transaction costs per se. So, herein the stablecoins came to the rescue. Well, the arguable rescue to cover the network of intermediate payments served to evade the US regulation, exploit the international reliability of USD and threaten the USD dominance worldwide.

For example, one of the most popular USD-pegged stablecoins are USDT (issuer: Tether) and USDC (issuers: Circle in collaboration with Coinbase) with over 113.7 bln. and 33.6 bln. in circulation respectively (as of July 19, 2024 [2]). Both are among the Top-6 (by market capitalization) cryptocurrencies circulated.

In short, the trades on USD-pegged stablecoins utilise USD as a medium of exchange in international settlements along with the absence of ledger records (due to the underlying technology of smart contracts) and regulatory tracing while posing risks not only to the USD market dominance but the stability of the entire financial system. These stablecoins build the house of cards based on the modern USD performance in global markets. Once being compromised it inevitably spurs the chain of collapses transferring financial shocks both to mainstream finance (or TradFi) and crypto markets.

Besides, authoritarian states like Russia and China amplify crypto to interfere with the US economy and exploit and threaten the USD's strength on the world stage.

Should the USD-pegged stablecoins be excluded and banned for criminal use including money laundering and financing of terrorism, the landscape of the crypto and its criminal vitality will be defeated. Once and for all.

References:

[1] Roshan Iyer, Adina Popescu (2023) “New Evidence on Spillovers Between Crypto Assets and Financial Markets”. IMF Working Paper WP/23/213.

[2] CoinMarketCap data (as of July 19, 2024).

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 115) by Dr. Olga D. Khon

Neither Bitcoin nor any other crypto asset could substitute the US dollar in international settlements. That’s an obvious fact despite too loud statements made by crypto fans.

Just because, if otherwise, they wouldn’t tie the biggest crypto success ever particularly with intersection and transformation into the appendix of the global financial system. Or simply put, with resource extraction from TradFi and the primary access toward the USD cash.

It all began with payment systems like PayPal, Visa and MasterCard. After which it spread to stock exchanges (following the Bitcoin Spot ETFs approval and crypto ETNs). And now it attempts to break into the essential bastion of mainstream finance’s stability — traditional banks.

Well, you heard it right, the crypto dreams to settle down within the network of the same intermediaries by the critics of which they justify their own creation, alleged uniqueness, and arguable benefits. That crypto is eagerly turning to the same TradFi markets. It craves acquiring the greater general public to be involved. Since beyond TradFi crypto is a batch of disrupted marketplaces with limited liquidity doomed to inevitable self-destruction.

But should the advantages of TradFi be clear, do you think crypto wants to follow the same level of financial compliance and regulation? Paradoxically, no. Crypto proponents at the breakdown shout about some unique regulation, which, in fact, reflects the absence of responsibility before the law and ordinary investors.

So, should the crypto be the tool they claim they are, such an actual alternative to mainstream finance (or TradFi), they wouldn’t yearn to bond tightly with so allegedly vicious, as far as they’re concerned, TradFi.

It’s time to acknowledge crypto markets are merely the ugliest and quite dangerous rudiment of mainstream finance.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 114) by Dr. Olga D. Khon

This week crypto turned its frantic criticism towards the German and US governments blaming on actions the industry opposes, namely, a few sales of Bitcoin (BTC) tokens previously seized from criminals.

First and foremost, the state agencies do the right thing: they sell assets on the regulated trading places called centralised exchanges (CEXs) proving the deal transparency and market prices.

Besides, the trades crypto so fiercely criticised are between 0,005% and 0,025% of total BTC in market circulation (around 19,72 mln. tokens as of today) or just 1k-5k against 19720 k.

Moreover, after the fourth Halving, about 450 new BTC tokens (0,45k) are still freshly minted and added to circulation daily (since 144 blocks per day are mined on average).

In terms of global markets such tiny sale deals should hardly be the reason for harsh fluctuations. They would remain in the margin of error.

Yet the crypto is different, it’s worse. In economic terms, this means crypto markets are almost completely inefficient, so any distinct player could impact the market price. Simply put, ordinary investors are at risk of frequent manipulations and near-inevitable losses.

It is the essence of vast inequality in crypto as well. Just think of numerous blockchain developers and originators, miners and validators, possessing hundreds of thousands and even millions of tokens versus ordinary investors. In reality, no one becomes a crypto whale or shark directly through crypto trading based on average capital and beyond shadow crypto activity involvement.

So, the latest crypto attack on the governments underpins one basic unspoken notion. Crypto doesn’t want anyone legally and transparently except themselves to cash out tokens. Given the plenty of tools to sell tokens opaque, circumventing law and regulations (thus, beyond visible market influence), the crypto industry is eager to force prices up and down when needed for their sole benefit and interests.

In a nutshell, crypto is a highly organised crime structure hiding behind misguided hard-woking ordinary investors losing their savings in the dangerous and even life-cost gamble…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 113) by Dr. Olga D. Khon

Have you noticed the ease with which blockchain proponents invert facts for their benefit? Let’s discuss the next example — Bitcoin Spot ETFs on the US market and their impact on crypto pricing.

On the one hand, crypto news outlets write about how popular these ETFs are, and why such rising demand pushes crypto prices up.

On the other hand, when markets go down, the same Bitcoin Spot ETFs’ popularity is applied to explain falling prices. For instance, when the crypto industry hesitates to reveal the genuine reasons for particular price drops such as financial abuse from the Russian regime aimed at sanction circumvention. Then, they argue that the popularity of ETFs leads to investor outflows, token sales off and, thus, price decreases. Albeit the latter is just a half-truth given that extra demand for Bitcoin Spot ETFs requires their issuers to buy more tokens and balance the market (for the case of direct token trade deals with no smart contracts’ tricks involved).

That sounds paradoxical, right? Why does crypto utilize one single factor to explain two opposite price movements?

The answer is trivial. Crypto often relies on massive confusion of the general public and hiding the truth.

Besides, these crypto allegations are based on the distorted analogy between the crypto markets and mainstream finance. Whilst crypto is a much more fragmented marketplace with a persistent lack of liquidity.

But crypto doesn’t want you to understand the actual state of the art while destroying the stability of the financial system and your future prosperity.

So, how long do we have to tolerate this fake show of crypto populists?

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 112) by Dr. Olga D. Khon

The more ‘blockchain’ and ‘crypto’ terms trace negative connotations with dozens of criminal indictments stated, the industry tends to promote other consumer-friendly notions among which smart contracts dominate.

Perhaps, it comes with the title “smart” the tool was named despite multiple evidence of AML/CFT obstruction, investor manipulations and facilitation of illicit finance. So, many blockchains represent themselves as smart contracts platforms (instead of primarily pointing to distributed ledger technology or crypto area) promising allegedly perfect solutions to the financial world.

Recalling blockchain basics, let’s debunk some popular myths about smart contracts:

1. Immutability. Originally the code was supposed to be immutable (once deployed it can’t be changed), albeit the advances in smart contracts allow the developers to provide alterations to the code.

2. Self-execution and Automation. Smart contract as a set of instructions requires an initiation by human-owned blockchain accounts for each code activation. Simply put, it’s a third-party-led execution for a fee-paid service.

3. Disintermediation. Smart contracts are built on intermediaries called blockchain oracles to be involved since the former can’t reach off-chain data (including crypto token prices or any real-world information) and have to apply for an external service. Besides, smart contracts are services written and chargeably deployed into blockchain by their originators who then collect fees from the users.

4. Legal Transparency. Smart contracts contradict AML/CFT and proper KYC checks by default since all the transactions they execute have no ledger records. Smart contracts implement a mechanism of simple updates of account balances for parties involved with no direct links to be revealed so that the asset tracing remains obscured.

5. Decentralization. Smart contract’s open source code is a single centralised point of vulnerability, once compromised, it opens the path for exploitation.

6. Data anonymization and Security. For anyone except the core blockchain developers and originators who trace and collect all the transaction information executed throughout their blockchain’s net of smart contracts (beyond regulation, business confidentiality and user consent).

When it comes to financial innovations, it should work on the improvement of the global financial system for everyone’s prosperity but not the limited groups of interested parties like blockchain developers and illicit actors who gain the source of law evasion worldwide. So, why should we still praise smart contracts — the very Colossus on clay feet?

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 111) by Dr. Olga D. Khon

Let’s recall some basics of blockchain today, and once and for all remind ourselves that claims of disintermediation (the absence of intermediates in blockchain space) are an intended misguidance.

First of all, what is blockchain?

It’s a network of blockchain nodes or, simply put, computers spread around the globe, that should store the copy of the ledger, transmit data and execute transactions.

Do these nodes run automatically by their mysteriously independent computer will?

No. They are deployed by their owners to receive block rewards and transaction fees as a part of blockchain economic incentives. These owners could be either institutional or individual but the former dominates tremendously.

In addition, there is a need for software that would connect these nodes and make them work in a rule-coordinated manner. However, there are creators of such software known as blockchain developers and originators who possess full control and are responsible for any software development and network protocol changes. They gain their profits from increasing public attention and use along with token price jumps.

Atop these underlying node networks, numerous derivative blockchains (the code-constructed intermediaries) are placed like sidechains, layers-2 and so on, as well as pseudo-disintermediate decentralised finance (DeFi) domain or subordinate services such as crypto bridges and mixers. All of which collect their extra fees and commissions. The majority of these shadow crypto intermediaries are run through so-called smart contracts, the lines of code aimed to execute routine tasks under “if-then” logic when the required conditions are met (see Note 108. «Smart-Contracts and Asset Tokenisation: The Dream Time for Illicit Finance»).

This rapid and uncontrolled distribution of crypto intermediaries throughout the world could not only conquer but destroy the body of the global financial system the way cancer cells act. So, do not forget blockchain is an aggressively interested intermediary.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 110) by Dr. Olga D. Khon

Yet again, the last wild crypto rally coincided with a stampede of corrupted money from Russia. Since Putin’s fifth term of presidency and the replacement of the minister of defence on the 13th of May 2024, the bribery prosecution of military commanders commenced.

According to analysts, those military authorities have not yet been affected, begun to sell their property and extract money from Russia. And, as we foresaw, all to be done through the favourite tool of Russian corrupt officials and criminals — the crypto-related channels. Bet those Russian military generals represent the most advanced ones in the ocean of crypto whales and fraudsters of our times.

We also heard the calls from Donald Trump running for presidency (and known for his bromance with Putin) to prioritize the crypto donations. The reasoning for crypto criminal use is quite clear. That is the complication of regulatory tracing and provision of suspicious finance into the legal financial system, including sanction evasion and election interference cases.

Notably, we should reflect on the consequences of the potential wide adoption of crypto, the purely speculative assets, that extract value from the global financial system to serve illicit finance. Given the serious inflationary pressure many governments have been confronted with for years, global financial stability is highly exposed to man-made (or, to be precise, blockchain-developers-made) price manipulation under the demand of unregulated interested parties.

Crypto allows illicit actors to execute almost everything, every crime of the scale they ever dreamt about but couldn’t proceed within mainstream finance. And, unfortunately, there is only one payer for all their illegal deeds — our everyday life under the stability of the global financial system and the prosperity of a democratic world.

So, one day, sooner than later, the current world order would have to pay the price for all crypto-facilitated crimes. The very payback time when no one wants but has to live in…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 109) by Dr. Olga D. Khon

Any conversation about smart contracts often ends up praising the alleged automatic execution with no intermediary involved. In fact, the public allure of smart contracts is just an overwhelming crypto promotion that hides the dark loopholes of this tool.

So, let’s try to foresee the key aspects of smart contracts and understand the damaging effects they bring to global anti-money laundering and counter the financing of terrorism (AML/CFT) efforts.

To begin with, we should recall claims of smart contracts to be self-executed computer code or programs based on simple “if-then” logic. Well, the automatisation of some routine tasks is not novel for financial services on which e.g. the banking industry has relied for years. Albeit with less public promotion of such smart technological moves.

As for modern smart contracts, they exist and interact solely within blockchains, primarily, Ethereum and other Ethereum Virtual Machine (EVM) compatible blockchains. That means they need to be deployed to these blockchains as well as being written in accordance with underlying standards on one of the preferred coding languages.

The deployment of smart contracts (to make it work) requires its originator to pay transaction costs (e.g. gas fees on Ethereum) which are higher than the ones set up for ordinary blockchain transactions.

Moreover, smart contracts can’t retrieve any off-chain data like token prices or any other information in regard to the real world. And, therefore, by default, smart contracts do require the involvement of third parties called oracles in blockchain who are supposed to provide all the off-chain information (gaining their extra fees).

Then, all the further operability the smart contracts provide exists within the underlying blockchains only. And here is the trick. Albeit transaction execution through smart contracts impacts the account balances’ updates for parties involved, there are no ledger records occurred. Simply put, no one (neither regulators nor the general public) knows who sends to whom and what amount of crypto tokens.

The only parties that are aware of all the interactions are core blockchain developers and originators who gained access to all the data of every smart contract ever deployed to their blockchain per se. Yet they escape any legal responsibility.

Thus, in terms of global AML/CFT policies, the smart contracts represent the black box of unlimited flows of assets transmitting throughout the world.

Given the existing scope of application for smart contracts from stablecoins, non-fungible tokens (NFTs), derivative tokens like meme coins, asset tokenisation, crypto bridges and mixers, layer-two blockchains, up to decentralised exchanges (DEXs) and the entire subfield known as decentralised finance (DeFi), the damaging effect for the global financial system is gigantic.

So, the current push for smart contracts-based tokenisation is just a dream time for illicit finance and surrounding criminal actors. But for this riot will have to pay not only the culprits but all of us…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 108) by Dr. Olga D. Khon

These days a few crypto figures attacked the US government for allegedly “killing innovations”? But why now?

Foremost, among these voices are former and acting participants of the Ethereum Foundation, the operation of which silently backs the aggressive interests of Russia since its origination (see Note 69. «Blockchain Origination: Timing Does Matter?..» and Note 102. «Crypto Backs the Interest of Russia»). With Russia fiercely dreaming of destabilizing all the grounds of the democratic world, crypto remains its very weapon.

So, we should clarify: if crypto is about innovations then it’s primarily criminal innovations to foster illicit finance and criminal activity worldwide. Money launders, terrorists, human and drug traffickers, corruptionists, war and other criminals, are all praising crypto.

Yet the crypto industry is famous for claims chanting itself. But losses ordinary investors suffered from the current Bitcoin Halving is another tragic example. Three weeks later, the Bitcoin price is at the one-month low and remains below the level fixed on the Halving day.

Unfortunately, thousands and millions of ordinary investors who lost their savings in the Bitcoin Halving fraud were victims of years-long manipulation. This time crypto promoters try to cover their criminal activity by shifting the public attention to targeting financial regulators so that Russia-backed crypto got its “Go” code to attack…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 107) by Dr. Olga D. Khon

China’s Xi visits Europe (France, Serbia and Hungary), and crypto endorses it. Prices are on a short rise this weekend outside major trading sessions. But have you noticed that China was amongst the first countries that severely banned crypto almost a decade ago?

Well, crypto, unfortunately, is quite a resultive tool to destabilise societies and financial markets around the globe.

No secret crypto is famous with autocrats for its destructive activity against democratic values and the Free world. We’ve seen enormous money laundering conspiracies executed throughout crypto with criminal proceeds facilitating corruption, terrorism, drugs and human trafficking.

Indeed, Russia is a mastermind of crypto but Russia has been a vassal of China for a long time.

For how long will the crypto remain the weapon of autocrats?

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 106) by Dr. Olga D. Khon

This Wednesday (May 01, 2024), the US Treasury imposed the next sanctions against Russia. They aimed to “degrade Russia’s Military-Industrial Base and Target Third-Country Support with Nearly 300 New Sanctions”.

And, quite expectedly, crypto prices shortly began to rise. We’ve observed the same pattern several times since the Russian full-invasion of Ukraine commenced. In brief, Russian authorities, each time suffering from sanctions that narrow their living space, try to channel their capital through crypto. In the short run, it boosts the demand and, thus, crypto prices. And, bet, there is nothing accidental in the following painful descent.

Such repeated price dynamics prove two things: 1) Crypto is the major tool for sanction evasion on a global scale for Russia; and 2) International sanctions against Russia do obtain the effect of inexorable forces, indeed.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 105) by Dr. Olga D. Khon

Crypto chants Bitcoin halving as a miraculous fetish for getting rich quickly, inviting more and more affected in crypto. Albeit halving occurs on the Bitcoin blockchain every 210,000 blocks or approximately every four years, this fourth halving has gone differently.

Indeed, during the current halving resumed on Saturday (April 20, 2024), the play on emotional exaggeration to boost public misguidance for anticipating price jumps was of little help. When you recall the last two pre-halving months, the bitcoin (BTC) price confronts any steady upward trend. It stuck in a wild rally of ups and downs (between $55k and $74k). It is hard to imagine how many ordinary investors lost all their money. Notably, BTC price substantially fell the week before halving.

It happened to disregard the date and approximate time of halving are known for sure — the block number (or height) 840 000. Given the speed of creating one block on the Bitcoin blockchain equals 10 minutes, the halving timing is a piece of public information disclosed since its creation.

Even after this halving had been formally recorded at 03:39 UTC on April 20, 2024, BTC price hesitated the following twelve hours (till 15:30 UTC) to reflect the first sign of growth (the same time the U.S. House of Representatives started to vote on long-anticipated Ukraine aid bill and the seizure of Russian frozen assets). This price volatility reminds us more of a manipulation done during the illiquid crypto market on weekends rather than a genuine post-halving effect.

So, crypto as the very last resort for sanction evaders, terrorists, and war criminals, will shortly face tremendous manipulations, unfortunately, at the expense of ordinary investors and the general public more broadly. We’ll foresee their desperate attempts to revive the Bitcoin halving as the major crypto myth inevitably crashed.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 103) by Dr. Olga D. Khon

Crypto chants Bitcoin halving as a miraculous fetish for getting rich quickly, inviting more and more affected in crypto. Albeit halving occurs on the Bitcoin blockchain every 210,000 blocks or approximately every four years, this fourth halving has gone differently.

Indeed, during the current halving resumed on Saturday (April 20, 2024), the play on emotional exaggeration to boost public misguidance for anticipating price jumps was of little help. When you recall the last two pre-halving months, the bitcoin (BTC) price confronts any steady upward trend. It stuck in a wild rally of ups and downs (between $55k and $74k). It is hard to imagine how many ordinary investors lost all their money. Notably, BTC price substantially fell the week before halving.

It happened to disregard the date and approximate time of halving are known for sure — the block number (or height) 840 000. Given the speed of creating one block on the Bitcoin blockchain equals 10 minutes, the halving timing is a piece of public information disclosed since its creation.

Even after this halving had been formally recorded at 03:39 UTC on April 20, 2024, BTC price hesitated the following twelve hours (till 15:30 UTC) to reflect the first sign of growth (the same time the U.S. House of Representatives started to vote on long-anticipated Ukraine aid bill and the seizure of Russian frozen assets). This price volatility reminds us more of a manipulation done during the illiquid crypto market on weekends rather than a genuine post-halving effect.

So, crypto as the very last resort for sanction evaders, terrorists, and war criminals, will shortly face tremendous manipulations, unfortunately, at the expense of ordinary investors and the general public more broadly. We’ll foresee their desperate attempts to revive the Bitcoin halving as the major crypto myth inevitably crashed.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 102) by Dr. Olga D. Khon

When it comes to any blockchain, its vast description goes to the consensus mechanism, meaning the rules and protocols for block producers to create blocks and receive rewards. In other words, the way how new crypto tokens are minted determines the blockchain token supply model.

For instance, Bitcoin is known for its years-long promotion campaign of its allegedly limited supply model (maximum of 21 mln. tokens) with the consequential reward halving (see (see Note 100. «Bitcoin Halving: Criminal Casino»). Or Ethereum claims its deflationary model when more tokens are burnt (as base gas fees) than the newly minted (as block rewards).

All such promotion campaigns representing each blockchain (incl. both layers one and two) as separate notions with their pros and cons are in vain. The essential feature is that the majority of blockchains (with top market cap, in particular) are interlinked into a unified blockchain token system through crypto bridges (based on smart contracts). Simply put, tokens from any blockchain could be wrapped into another blockchain token standard, shifting token supply between networks. So, any so-called limited supply model in reality swiftly and hiddenly transforms into a skyrocketing one.

Thus, the vocal diversity of consensus mechanisms with a bunch of forks (blockchain updates) and tons of info pages, works for the distraction of the general public, investors, and regulators. While it’s just a single blockchain-minted crypto global fraud threatens financial compliance worldwide.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 101) by Dr. Olga D. Khon

Crypto advocates so desperately promote the next Bitcoin halving scheduled in April 2024 to promise a further crazy boom in Bitcoin (BTC) prices. They apply this to artificially provoke excess public demand and agiotage of crypto-addicted people in advance. It is nothing more than regular market manipulation.

As crypto proponents explain, their logic is a basic market explanation duplicated from mainstream finance: price jumps in exchange for an apparent BTC token supply decline. Although they forgot to mention a crucial discrepancy in the crypto market regarding mainstream functionality. Simply put, the crypto market is a different one.

To recall, the Bitcoin blockchain operates on a Proof-of-Work (PoW) consensus mechanism where block producers (or miners) receive rewards in BTC for each block broadcasted to the ledger.

Herein Bitcoin halving stands for a process of block mining rewards to be split in half around every four years (or, more precisely, each 210 000 blocks). It presumes that BTC token supply is going to decrease and, thus, spur prices following the growing demand.

Well, in mainstream finance this explanation has solid ground but not in the crypto space. The trick in crypto hides in unlimited bridge wrappings that substitute extra token supply. Should be multiplied by multi-level token collateralization in decentralized finance (DeFi) and intra-layer asset tokenization, the token supply could be galvanized indefinitely. At least, until the crypto market painfully collapses.

Crypto assets have already disrupted international financial compliance while accomplicing the most outrageous crimes against humankind (human trafficking, drug trafficking, terrorism, child sex abuse, and war crimes). In this row, Bitcoin halving is a vicious phenomenon criminal casino.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 100) by Dr. Olga D. Khon

Bitcoin Spot ETFs became the welcome door for crypto to mainstream finance. Despite crypto fans arguing it’s an equal opportunity to participate in a crypto race, such funds make regular investors quite vulnerable.

To begin with, Bitcoin Spot ETFs are traded on mainstream stock exchanges during working days only, from Monday to Friday. While Bitcoin (BTC) as these ETFs’ underlying asset is traded 24/7 on numerous fragmented marketplaces worldwide. Besides, managing companies behind Bitcoin Spot ETFs are the largest BTC holders (or crypto whales) that easily impact token prices on partially illiquid crypto markets.

It follows that regular investors of Bitcoin Spot ETFs are subject to market manipulations and exploitations, and limited in their investment opportunities because:

1) Market manipulations are easily executed with relatively small token possessions beyond working hours (during weekends and night periods) with lower liquidity. So, management of the fund could accomplish speculative trades during off-working hours profiting for itself at the expense of its clients;

2) Even when the fund is prudent, due to the essence of blockchain transactions, each trading move (buy and sell deals) is disclosed beforehand to so-called block producers (miners and mining pools on the Bitcoin blockchain). Thus, there are plenty of opportunities for arbitrage gainers and maximal extractable value (MEV) collectors to overbid Bitcoin Spot ETF trades (e.g. shift the price to wishful levels) and harvest, again, at the expense of ordinary investors.

In a nutshell, Bitcoin Spot ETFs were never intended to be a transparent and safe vehicle for investment. Instead, it’s the manipulative switch that provides enormous fiat liquidity to crypto space and illicit actors to overcome financial regulation at times of geopolitical tensions, war conflicts, and international sanctions.

Unfortunately, Bitcoin Spot ETFs are a false move with negative consequences for all of us to disregard any connections or interest in crypto.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 99) by Dr. Olga D. Khon

Last week, curious article with a sharp title “Bitcoin ETFs approval — The Naked Emperor’s New Clothes” by Ulrich Bindseil and Jürgen Schaaf was published on the European Central Bank (ECB) blog posts. And I do recommend everyone to read this work.

Though our talk today is not about the article context but an instantaneous reaction from the crypto industry. Right after the ECB publication, multiple crypto news outlets released their discontent toward ECB. The bunch of such crypto offensive reminds us more of a populism that plays on concept shifting and public manipulation. The quite despicable thing that decent financial regulators cannot afford.

Thus, crypto often overcomes ethical and legal boundaries gaining on a higher demand from illicit actors (criminals, terrorists, human trafickers, etc.). Impudence, aggression, easy money are in the primary arsenal of crypto bullies. Bullying is the manner in which crypto proponents and other crypto-addicted individuals attack others for any kind of opposition to crypto. Particularly, when the criticism of crypto is precise and correct.

Crypto is an inquisition that tolerates no dissent. Yet it’s up to our modern civilization to prove that genuine knowledge and professionalism always win.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 98) by Dr. Olga D. Khon

Sam Altman’s (OpenAI, the company behind ChatGPT) Worldcoin is just a derivative ERC-20 token issued on Ethereum by the means of smart contracts. This comes with several comments to general misinterpretation of Worldcoin (WLD) that:

1) has no distinct underlying blockchain and is runned through Ethereum charged service (smart contract’s deployment);

2) Transfers are not transparent and publicly untraceable (since they have no records on Ethereum ledger);

3) Transactions are exceptionally disclosed to Ethereum core blockchain developers and originators (beyond user consent);

4) Is a purely speculative asset exists, trades and circulates through Ethereum blockchain (and is prone to spikes in transaction fees due to high transactional demand and blockchain congestion).

Thus, in a wake of crackdown against money laundering, tax and sanction evasion, war crime, terrorism, and other illicit activity within mainstream finance, boosting crypto volume trades and token prices is nothing but the proof of one simple truth. That’s the blockchain-minted crypto assets are favorite and, perhaps, even last resort for global AML/CFT violations which facilitate the most outrageous crimes against humankind.

So, the current hype of Worldcoin is just the next false excuse for a greater damage the crypto will bring to the global financial system in near-future.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 97) by Dr. Olga D. Khon

Some claim smart contracts are autonomous. But, on the contrary, smart contracts do demand human-based interaction and governance.

Being a computer code on Ethereum, smart contracts could be run (process any transaction) only in the aftermath of the ‘call’ received from users’ externally owned accounts (EOAs). Simply put, they require primary human participation to be involved. Given the same degree of misinterpretation, one could identify mobile banking applications as self-executed programs like the promo of smart contracts does.

Besides, as a computer program, smart contracts are created by human beings, known as blockchain developers, who deploy them into blockchain and pay initial gas fees (transaction costs on Ethereum) for this operation.

Due to the plenty of opportunities the smart contracts provide for asset obscuration and money laundering, public promotion of such tools is extremely harmful to the global financial system. Since it facilitates illicit activities worldwide.

To recall, transactions executed through smart contracts have no records on Ethereum Mainnet’s public ledger. So, they are not traceable by ordinary investors or regulatory bodies. In addition, smart contracts could batch multiple transactions and broadcast them as a single one to the ledger, which also diminishes the informational value of such records.

Moreover, smart contracts serve as the basis for multi-sig accounts when several individuals or entities hold a joint account from which they altogether execute blockchain transactions. Thus, it complicates the resulting checks of transactional end-users (both initiators and recipients).

Notwithstanding obfuscation techniques that smart contracts constructed for the general public and regulators, all the hidden and detailed information is apriori available to Ethereum core blockchain developers and originators. The latter has full access to any smart contract (incl. data on illicit finance and criminal activities) ever deployed into the Ethereum ecosystem.

Herewith Ethereum core developers and originators play as accomplices to numerous illicit actors for whom blockchain is a massive cover-up. This is the «Mirror of Shadows» in smart contracts where reality is hugely distorted …

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 96) by Dr. Olga D. Khon

Crypto promotion is based on the hype terms. In the beginning, it was “crypto” and “blockchain” themselves. As far as they absorb a negative connotation, the crypto proponents utterly switch to a new fashion, namely, digital finance and artificial intelligence.

These terms represent quite substantial, urgent, and rapidly evolving areas. Until they play as a set-up for the crypto destructive activity.

Such misguidance became more dangerous within the university education. Students could be attracted by the promising notion of digital finance. But receive only a distorted chunk with a lack of quality that is delivered by senior crypto accomplices who dream of preparing the new army of crypto slaves.

Everything would be fine except this criminal substitution would destroy the career and future of our younger generation.

So, please be cautious while meeting “digital finance” in the title, and distinguish the case when the crypto propaganda is concealed by it.

PS. As a lecturer in digital finance, I will never cooperate with crypto or teach its pseudo-scientific premises!

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 95) by Dr. Olga D. Khon

Crypto companies oppose the prospects of reporting on their use of crypto mixers to regulators. That’s strange since they already do the same but before unregulated third-party — core developers and originators of the underlying blockchain. Should the mixer be built on Ethereum, then it’s the Ethereum Foundation.

The trick is in the essence of crypto mixers as paid services operating through smart contracts. Although crypto mixers aim to obscure asset flows and end-user recipients, the core blockchain developers and originators have full access to any smart contract deployed to the blockchain. So, the data is automatically disclosed outside the crypto mixer’s domain.

Simply put, the Ethereum Foundation beyond mixers’ developers and executives is well aware of each transaction executed through crypto mixers (including those facilitating illicit activities). Yet Ethereum Foundation avoids legal responsibility for disruption of global AML/CFT policies, tax avoidance and sanction evasion implemented through their blockchain.

Thus, if crypto projects apriori expose the detailed mixing data to core blockchain developers and originators, why do they oppose a disclosure toward the trustworthy regulators? What do you think is it just a syndrome of the weak against the strong or a pure bluff?..

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 94) by Dr. Olga D. Khon

When Coinbase launched its layer-2 “Base” in August 2023, it hardly remained a representative of crypto centralised exchanges (CEXs). Since all the user transactions are sent through Base forwarding by crypto bridges to the Optimism blockchain and, thus, Ethereum. Simply put, the same way decentralised exchanges (DEXs) work under the risks of user data leak and manipulation.

Thus, all Coinbase’s Base user transactions are pending in a single Oprimism’s mempool, and executed by an unauthorised and unregulated crypto intermediary. It represents a coordinated and constant user data breach outside the Coinbase domain. Yet Coinbase consents to pay extra fees for Optimism services.

To recall, Optimism is a type of layer-2 scalability tool on Ethereum known as optimistic rollups. They rely on smart contracts’ functionality with a bunch of asset obfuscation techniques and money laundering consequences (see Note 89. «Smart Contracts: Wolf In The Sheep’s Clothing» for more details).

Besides, investors are at risk the most. Given the nature of smart contracts and blockchain transactions, each trade with info on end-user recipients and amounts transmitted becomes disclosed to Optimism and, thus, Ethereum core blockchain developers and originators. At least, they become aware of the current demand and supply on the Coinbase marketplace, so as the closest impact on market prices and future trends. And could intervene in the market by excess arbitrage, wash trading and manipulation.

Unfortunately, the matching of user’ full identities to their financial records is a piece of cake as well, while it remains non-transparent to the regulatory bodies. Although neither Coinbase nor Optimism and Ethereum bear legal responsibility for data exploitation of Coinbase’s users.

Herein Coinbase is acting innocent, promoting rather innovative agenda than tricks for immense profit making. While it’s innovative, it should be placed in a series of innovative tricks to evade financial compliance.

Well, Coinbase keeps a good face while playing foul, but the great film director Stanislavski would say: «I don’t believe you!»

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 93) by Dr. Olga D. Khon

The most discouraging thing in crypto promotion is the way it presents every single token and project as an allegedly separate notion. While tokens all over the most popular blockchains are strictly tightened together. Through the vast net of smart contracts under the visibility of crypto bridges, they depict one single crypto knot.

So, there is no room for proper financial compliance within every blockchain-minted token (or so-called cryptocurrency) at all. And Bitcoin (BTC) and Ether (ETH) are no exception.

More importantly, bridges serve for the nullification of crypto assets’ tracking history so far. Once submitted to the bridge (and its smart contract’s operability) the token becomes “financially cleared”.

For instance, illicit financial flows gone through privacy coins, like Monero (XMR) with its anonymous and untraceable transactions, could get extra laundering by bridges and freely operate throughout public blockchains (incl. Bitcoin and Ethereum).

Imagine, illicit actors and criminals could even cash out their laundered illegal proceeds by selling their BTC tokens directly to crypto funds — providers of Bitcoin Spot ETFs given the current “Pyrrhic victory” of the latter.

Besides, token transfers through bridges work as a substitution for crypto trade deals beyond the imminent impact on market prices. It’s one of the features the biggest crypto holders (aka whales) are most interested in.

Meanwhile, crypto bridges provide the greatest weakness of blockchain while storing custody under the original tokens sent and minting the wrapping version of it. The exploitation of the bridge’s smart contract code could disrupt the entire system. To recall, the Ethereum native token Ether is not an ERC-20 standard its smart contracts operate on. Thus, at the heart of the Ethereum ecosystem’s functionality vitally grounds the ETH-WETH bridge (WETH is wrapped in Ether or Ether’s ERC-20 version). The other notable example is the BTC-wBTC bridge that works on an invisible push of Bitcoin into Ethereum’s domain (wBTC is a wrapped Bitcoin or Bitcoin’s ERC-20 version).

This substantial network of crypto bridges reminds me of a devious octopus that spread its rapacious fingers to enormous market manipulation and asset obscuration, indeed.

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 92) by Dr. Olga D. Khon

Crypto agony towards Bitcoin Spot ETFs has reached its current destination, a coveted but quite shaky one. Notably, the day before the SEC approval was announced, crypto accomplices couldn’t resist violating the law.

The X (former Twitter) account of SEC Chairperson Gary Gensler was hacked to post a false statement that the approval has been made to boost agiotage on crypto markets. It could hardly be interpreted as a respect to regulators and descent law responsibility.

Given the desperate battle for extra money the largest crypto funds delivered for months, the decision could be expected. However, it represents a colourful example of the exploitation of many (the general public) by the very few (crypto whales accompanied by core blockchain developers and foundations).

To remind you, crypto funds substantially invested into crypto tokens can’t exit the staled poorly liquid markets being unnoticed and extra panic to be created. At least, they tried to avoid losses while gathering efforts to push their future business prosperity at all costs, mainly, fresh retail investors. This, unfortunately, is what we are about to foresee shortly.

Moreover, Bitcoin Spot ETFs would accompany stablecoins in cash provision and cross-border transition to the crypto domain disregarding the black holes in financial compliance, particularly, global AML/CFT policies. Besides, they should follow the Bitcoin market prices deeply prone to daily manipulations due to the nature of token trades. As deals are stored in blockchain transactions, their info (incl. Nearest price movements) is available to block producers (not the ordinary users) beforehand while being placed into the mempools (intermediary pools of pending transactions).

Nevertheless, the regulation is evolving into a holistic perspective where the systemic risks and stability damages the crypto brings to the global financial system become more transparent. So, even under Bitcoin Spot ETFs, crypto agony is yet inexhaustible and comes to an end such as any unrighteous deed…

Published on Medium.com  "TradFi and DeFi: Broaden Horizons" (Note 91) by Dr. Olga D. Khon