Finastra is the third largest financial technology company in the world. The firm was formed in late 2017 through the combination of D+H and Misys, after Vista Equity Partners acquired Misys in June 2012 and subsequently purchased D+H in 2017.

The company has offices in 42 countries with U.S. $2.1 billion in revenues. The company employs over 10,000 people and has over 9,000 customers across 130 countries

Problem statements 1 : Engagement Channels

Extend banks’ current level of engagement with their customers on new platforms/channels Few examples: -Amazon Alexa -Google Home -Apple Siri.

Context

The next mainstream computing platform may be voice-based computing. According to a new state of the industry report from VoiceLabs, it’s estimated that there will be 24.5 million voice-first devices shipped which will lead to a total device footprint of 33 million devices in circulation. Voice-first devices includes products like Amazon Echo, Amazon Tap, and Echo Dot, as well as later arrivals like Google Home, for example. Next generation bankers require different type of banking experience. Think about all the platform/channel possibilities that are available on the market. How would you engage customers with the help of these? How would you take the potential advantages of these new platforms?

Size of the problem

Medium

Solution Domain

DC, Retail

Notable 3rd party solutions/components to be used

• Conversation one : https://conversation.one
• Dialogflow : https://dialogflow.com

Example current solution

1. Amazon assistant
2. Google assistant
3. Siri

Ideal demo/presentation

Solution description, live demo

Development resources

Database, provided by Finastra Labs, Fusion Fabric Cloud, free to use available 3rd party tools

Background reading

1. https://www.voicecities.com/google-home_amazon-alexa-skill/development
2. https://developers.google.com/actions/
3. https://www.smashingmagazine.com/2017/05/build-action-google-home-api-ai/
4. https://developer.amazon.com/alexa-skills-kit/alexa-skill-python-tutorial

Problem statements 2 : Machine Learning Insights

Extend banks’ current level of insight to their customers with machine learning models.

Few examples on potential targets:

• Micro targeting clusters.
• Financial health index representing financial wellbeing comparable to peers.
• Sales affinity to specific products.
• Churn potential.

Context

Banks area accumulating vast amounts of data on their customers. Yet the customers are lacking insight into their financial health and banks are missing on cross sell opportunities. Understanding what customers want, knowing how to make a step forward even before the customer thinks about leaving the bank is a really challenging duty of banks.

Machine learning has had fruitful applications in finance well before the advent of mobile banking apps, proficient chat bots, or search engines. Given high volume, accurate historical records, and quantitative nature of the finance world, few industries are better suited for artificial intelligence. There are more uses cases of machine learning in finance than ever before, a trend perpetuated by more accessible computing power and more accessible machine learning tools (such as Google’s Tensorflow).

Today, machine learning has come to play an integral role in many phases of the financial ecosystem, from approving loans, to managing assets, to assessing risks. Yet, few technically-savvy professionals have an accurate view of just how many ways machine learning finds its way into their daily financial lives.

How would you use the available data to enhance customer experience, boost cross sell or simply to understand customer behaviors?

Size of the problem

Huge

Solution Domain

Machine Learning, Retail banking

Notable 3rd party solutions/components to be used

• Python software environment for statistical computing : https://www.r-project.org/
• Weka is a collection of machine learning algorithms for data mining tasks https://www.cs.waikato.ac.nz/ml/weka/
• RapidMiner is a software platform for analytics teams that unites data prep, machine learning, and predictive model deployment : https://rapidminer.com/
• Modernize data science – from data discovery to machine learning and application development. https://www.ibm.com/products/spss-modeler

Example current solution

1. Sentiment analysis: https://neticletech.com/ https://www.meltwater.com/uk/
2. Recommendation system: https://medium.com/netflix-techblog/netflix-recommendations-beyond-the-5-stars-part-1-55838468f429
3. Roboadvisor: https://www.betterment.com/
4. Fraud detection: https://www.sas.com/en_us/software/fraud-management.html

Ideal demo/presentation

Solution description, live demo

Development resources

Database, provided by Finastra Labs, Fusion Fabric Cloud, free to use available 3rd party tools

Background reading

1. https://www.udemy.com/python-bokeh/?siteID=SAyYsTvLiGQ-sTNOg5UleGsQ8MQMuXIdAQ&LSNPUBID=SAyYsTvLiGQ
2. https://www.datacamp.com/courses/data-visualization-with-ggplot2-1?tap_a=5644-dce66f&tap_s=93618-a68c98
3. https://www.analyticsvidhya.com/blog/2015/07/guide-data-visualization-r/

Problem statements 3 : Data Visualization

Enrich banks data visualization to gain insight, prepare decisions. For example, any VR platforms like HoloLens.

Context

The concept of using pictures to understand data has been around for centuries, from maps and graphs in the 17th century to the invention of the pie chart in the early 1800s.

It’s technology, however, that truly lit the fire under data visualization. Computers made it possible to process large amounts of data at lightning-fast speeds. Today, data visualization has become a rapidly evolving blend of science and art that is certain to change the corporate landscape over the next few years.

With big data there’s potential for great opportunity, but many retail banks are challenged when it comes to finding value in their big data investment.

Because of the way the human brain processes information, using charts or graphs to visualize large amounts of complex data is easier than poring over spreadsheets or reports. Data visualization is a quick, easy way to convey concepts in a universal manner – and you can experiment with different scenarios by making slight adjustments.

Data visualization can also:

• Identify areas that need attention or improvement.
• Clarify which factors influence customer behavior.
• Help you understand which products to place where.
• Predict sales volumes.

How would you take the advantages of new platforms in order to show a better picture of available data? How would you support decision making with the help of data visualization?

Size of the problem

Medium

Solution Domain

Visualization, Data

Notable 3rd party solutions/components to be used

• Python software environment for statistical computing : https://www.r-project.org/
• Harness the power of your data : https://www.tableau.com/
• Modern Visualization for the Data Era : https://plot.ly/
• JavaScript library for manipulating documents : https://d3js.org/

Example current solution

1. https://www.ted.com/talks/hans_rosling_shows_the_best_stats_you_ve_ever_seen
2. http://christopheviau.com/d3list/

Ideal demo/presentation

Solution description, live demo

Development resources

Database, provided by Finastra Labs, Fusion Fabric Cloud, free to use available 3rd party tools

Background reading

1. https://www.udemy.com/python-bokeh/?siteID=SAyYsTvLiGQ-sTNOg5UleGsQ8MQMuXIdAQ&LSNPUBID=SAyYsTvLiGQ
2. https://www.datacamp.com/courses/data-visualization-with-ggplot2-1?tap_a=5644-dce66f&tap_s=93618-a68c98
3. https://www.analyticsvidhya.com/blog/2015/07/guide-data-visualization-r/

Problem statements 4 : Open Banking

Build business scenarios for banks to be able to leverage the potential of PSD2 open banking

For example:

• Account aggregation
• net wealth
• up/xsell.

Context

The first Payment Services Directive (PSD1) was adopted in 2007. This legislation provides the legal foundation for an EU single market for payments, to establish safer and more innovative payment services across the EU. The objective was to make cross-border payments as easy, efficient and secure as 'national' payments within a Member State.

Since 2007, this Directive has brought substantial benefits to the European economy, easing access for new market entrants and payment institutions, and so offering more competition and choice to consumers. It offered economies of scale and helped the Single Euro Payments Area (SEPA) in practice. The first PSD has meant more transparency and information for consumers, for example about execution time and fees; and it has cut execution times, strengthened refund rights, and clarified the liability of consumers and payment institutions. A very tangible benefit is that payments are now easier and quicker throughout the whole EU: payments are usually credited to the payment receiver's account within the next day.

How will PSD2 allow consumers and merchants to benefit fully from the market? What can be the greatest benefits of PSD2 for customers? Get the most out of this Directive and show its possibilities.

Size of the problem

Huge

Solution Domain

PSD2, Retail

Notable 3rd party solutions/components to be used

• Github project : https://github.com/OpenBankProject/OBP-API/wiki/PSD2-Sandbox
• MKB portal sandbox : https://portal.sandbox.mkb.hu/
• Open Bank Project PSD2 sandbox : https://psd2-api.openbankproject.com/
• Nordics API-s : https://developer.nordeaopenbanking.com/
• Fidor API-s : https://www.fidor.com/solutions/developer
• Swedbank API-s : https://www.swedbank.com/openbanking/
• Danskebank API-s : https://danskebank.com/openbanking
• SEB API-s : https://developer.baltics.sebgroup.com/landing

Example current solution

1. https://webforms.hsbc.co.uk/ConnectedMoney/
2. https://www.yolt.com/

Ideal demo/presentation

Solution description, live demo

Development resources

Database, provided by Finastra Labs, Fusion Fabric Cloud, free to use available 3rd party tools

Background reading

1. https://www2.deloitte.com/content/dam/Deloitte/cz/Documents/financial-services/cz-open-banking-and-psd2.pdf
2. https://www.investopedia.com/terms/o/open-banking.asp
3. https://www.smashingmagazine.com/2017/05/build-action-google-home-api-ai/
4. https://developer.amazon.com/alexa-skills-kit/alexa-skill-python-tutorial

Problem statements 5 : Sustainable Finances

Help retail end users to get a better understanding of their financial health and to build a sustainable financial future for themselves

For example:

• VR/AR/Digital Assistant,
• Machine learning predictions,
• IFTTT

Context

Financial health is a term used to describe the state of one's personal financial situation. There are many dimensions to financial health, including the amount of savings you have, how much you are setting away for retirement and how much of your income you are spending on fixed or non-discretionary expenses. An individual’s financial health may be measured by a variety of metrics. A person’s savings and overall net worth represent the monetary resources at their disposal for current or future use. These can be affected by debt, such as credit cards, mortgages, and auto and student loans. Financial health is not a static figure as it changes dependent on not only the individual’s liquidity and assets, but the fluctuation and inflation of prices of goods and services over time.

For example, an individual’s salary might remain constant while the costs for gasoline, food, mortgages, and college tuition increase. Despite their initial financial health, the individual may lose ground and lapse into fiscal decline if they do not keep pace with rising costs of commodities.

Potential Elements of a Financial Plan :

• Financial goals
• Personal net worth statement
• Cash flow analysis
• Retirement strategy
• Comprehensive risk management plan
• Long-term investment plan
• Tax reduction strategy
• Estate plan

How would you support customers to have a better insight of their finances of their financial health? How would you educate end users to be more conscious about planning for future?

Size of the problem

Huge

Solution Domain

AR,VR,ML, Retail

Notable 3rd party solutions/components to be used

• 3D modelling (Unity) : https://unity3d.com/
• Connect apps with IFTTT : https://ifttt.com/
• Apple AR kit : https://developer.apple.com/arkit/
• Google ARCore : https://developers.google.com/ar/develop/java/quickstart

Example current solution

1. Holographic Workstation for financial trading: http://8ninths.com/case-study/citi-holographic-workstation/
2. VR wealth management: https://www.comarch.com/finance/news/virtual-reality-in-wealth-management/

Ideal demo/presentation

Solution description, live demo

Development resources

Database, provided by Finastra Labs, Fusion Fabric Cloud, free to use available 3rd party tools

Background reading

1. https://www.youtube.com/watch?v=khavGQ7Dy3c
2. https://medium.com/coinmonks/arcore-tutorial-21d67fce04dd
3. https://developer.apple.com/arkit/
4. http://blog.theknightsofunity.com/unity-vuforia-guide/
5. https://www.udemy.com/create-augmented-reality-apps-using-vuforia-in-unity-sdk/

Reward

Direct entry into the Idea Fest finals and a chance to win grant upto 7 lakhs depending on the stage of your idea, subject to the review and selection by the KUSM internal panel of judges.