Artificial Intelligence in Financial Services (special track)



The implementation of artificial intelligence (AI) based systems in financial services is becoming more and more widespread mainly due to the large amount of available data and more affordable computing capacity. AI is being used in financial services in areas such as trading, asset management, lending (in this particular area can AI be very effective in creditworthiness assessment) and crowdfunding. AI is also very helpful in fraud or money laundering detection or in uncovering terrorist financing. Currently AI is also being integrated into distributed ledger technology based finance (decentralized finance) and in smart contracts. The AI usage in finance brings many benefits not only for the financial services providers themselves by increasing the overall efficiency, reducing costs, enhancing productivity or allowing more effective allocation of human resources, but also for the end customers who are provided with more economical and higher quality services or wider selections of more personalized and innovative products. However there are also many potential risks or not yet answered questions connected to the AI usage. These risks emerge mostly from the data processing and the problematic explainability of the outputs from such processing. There are also no clear and binding rules concerning the accountability of the AI for these outputs. Uncertainties are also being recognized in the matters such as the possible algorithmic bias and discrimination of the AI outputs or systematic errors in data collection, their analysis and interpretation. The AI systems should be provided with robust, secure and resilient risks assessment and management, and the privacy and confidentiality of the personal data should be duly protected. Especially dubious may be the cross-border transfers of financial data (which may include personal data or data covered by banking secrecy) and their cross-border processing. It can be argued that there is not sufficient international framework in place, which would prevent misuse of personal data or deal with different regulatory standards concerning cross-border data transfers. Considerations are also given to the question, whether there should be an explicit regulatory framework that would require licensing of the AI systems used in financial services and such framework would grant power to relevant authorities to oversee such technologies and systems. The panel AI in finance will tackle the mentioned issues and introduce experts in areas such as:

Dr Joseph Lee, University of Manchester, UK

Dr Vincenzo Bavoso, University of Manchester, UK

Prof Aline Darbellay, University of Geneva, Switzerland

Prof Manuela Geranio, University of Bergamo, Italy

Prof Antonios Karaiskos, University of Kyoto, Japan

Iota Kaousar Nassr, Directorate for Financial and Enterprise Affairs, OECD

Mattias Levin, Deputy Head of Digital Finance Unit, European Commission

Marco Enriquez, U.S. Securities and Exchange Commission, Senior Applied Mathematician