Regulatory Compliance in AI Regime : Banks and FinTech

Tiivistelmä – Referat – Abstract Post the financial crisis of 2008, European Union has introduced a plethora of laws to reform the financial system and make it further resilient. While the crisis led to financial reforms that have created heavy load of compliance, it also created a field for innovation led financial services called Fintech. In the post-Covid-19 era, the need for financial institutions and supervisors to speedily and efficiently deal with compliance has become more pronounced, as they brace for the impact of pandemic and focus on other critical tasks. The combination of regulatory compliance load on one side and innovation on other side have made the role of AI critical to regulatory compliance and supervision. On this premise, the thesis discusses existing role of AI and the challenges in successful deployment of AI where it can be scaled to exploit all its abilities. The challenges in deployment of AI are two fold – one that relate to its role in compliance with financial governance framework including AML, PSD2, MiFID II and GDPR etc. requirements, and other that deals with the role of AI within compliance procedures such as reporting, following up with regulatory requirements and policies etc. The discussion aims to identify the gaps in technology such as black box problem and inductive bias in AI, as well as regulatory framework that hamper the deployment and exploitation of AI in compliance and supervision of financial institutions. At the same time, innovations such as RegTech and SupTech enable AI to provide fast solutions to banks, Fintech and supervisory authorities. The technological and regulatory challenges of AI are identified by doing empirical research and applying legal dogmatics, as well as considering socio-economic factors affecting the financial industry. The discussion also notes the vision of a Digital Europe and how the recently announced policy discussions such as the AI strategy, Data Strategy, Cloud Initiative, Digital Finance Strategy etc make a profound impact on the gaps identified, but also leave exposure to other possibilities such as lengthy process of adoption, implementation and testing of these policies. The discussion concludes that successful adoption of the proposed laws, provisions for financial industry in the AI strategy and new and innovative methods such as data ethnography can together solve the technological and regulatory challenges identified as hinderance to scaling up AI role in regulatory compliance