Financial technology (FinTech) refers to a set of technologies that seek to improve or automate financial services. These services can only internally affect the financial company itself to make it more competitive or they can also affect its clients to allow them to better manage their operations and assets. Therefore these technologies can cover a very wide range of services. The financial industry in general follows with great interest the technological advances, and it is evident that financial technologies have caused a disruptive change in the last years without precedents in the sector. Big banks such as JP Morgan or Bank of America have been early adopters of disruptive technologies. With no doubt machine learning is one of the technologies that has transformed this sector the most as the available data is abundant. Thus, we can find applications to analyze the risk levels of an operation or client, product recommendation systems for investors and clients, analysis of economic trends, financial coaching, prediction of customer abandonment ... Some examples that give an idea of success of FinTech can be found in the Bank of America whose financial assistance bot reached one million users in three months, or in JP Morgan that thanks to the automatic analysis has managed to release 360,000 hours of workload annually. According to the EY FinTech Adoption Index (ey.com.), FinTech users increased from one in seven digitally active consumers in 2015 to one in three in 2017. However, almost all machine learning application in FinTech must deal with sensitive and risk-taking operations. For this reason FinTech is specially challenged and the industry demands new conditions for the operation of these algorithms. These conditions involve issues such as data Trust, Fairness, Privacy, Trustworthy and Explainable data analysis at all stages in the machine learning project pipeline: from data preparation to deployment.
We encourage submissions from, but not limited to, the following list of topics in relation to FinTech:
Two types of contributions are admitted:
According to the ECAI reviewing process Scientific papers will be evaluated based on their scientific value: relevance, significance of contribution, impact, technical quality, scholarship and quality of presentation. Highlight papers are evaluated against the same criteria although, Relevance, Significance, Novelty and Technical quality, refer to the work reported and not the paper itself, and the paper would be of interest to the attendees.
All papers must be original and not simultaneously submitted to another journal or conference.
All kind of papers should be formatted according to the ECAI2020 formatting style. Details are available at ECAI2020 website.
Submission and review of papers for this Workshop will be managed via Easychair: https://easychair.org/conferences/?conf=trustfintechai20
Every workshop participant must register for the ECAI workshop program. Workshop registration will include workshop attendance, lunch, and coffee-breaks. There will be “workshop-only” registration (one-day and two-day options), and a reduced registration fee for those who also register for the main conference. The registration fees and deadlines will be announced on the ECAI website.
Extended versions of selected papers will be published in a Special Number of International Journal of Interactive Multimedia and Artificial Intelligence to be published in 2021. From 2015 to 2018 IJIMAI was indexed at Web of Science through Emerging Science Citation Index. This year, Clarivate Analytics has accepted the inclusion of IJIMAI in the Journal Citation Reports.
A prize of 200 euros, supported by Everis Spain , will be awarded to the best paper of the workshop.
The conference will be held in Santiago de Compostela (Spain).
All questions about submissions should be emailed to berta.guijarro@udc.es
Paper submission deadline: March 15th, 2020
Paper decision notification: April 15th, 2020
TrustFinTechAI workshop: June 8th, 2020