BCBS published a high-level summary of an industry workshop on the governance and oversight of artificial intelligence and machine learning in financial services. The Supervision and Implementation Group (SIG) of BCBS held this workshop on October 03, 2019. With regard to unique risks posted by artificial intelligence and machine learning, participants discussed how best to deal with ethics and bias, given that these issues have broader scope than that which is within the remit of prudential authorities. It was discussed that, while existing governance frameworks and policies are generally considered to apply to artificial intelligence and machine learning models, there may need to be further refinements.
The workshop, which was chaired by Mr. Arthur Yuen, Deputy Chief Executive of HKMA. primarily covered the use of artificial intelligence and machine learning in the banking sector. The SIG met with senior representatives from internationally active banks and associated industry associations, consulting and technology firms and other public authorities to discuss how banks are leveraging artificial intelligence and machine learning technologies to better manage risk or offer new and innovative financial services; also discussed were the associated challenges related to risk governance, data management, and engagement of third-party service providers. The SIG also discussed how bank supervisors and other official sector bodies are approaching the risks arising from the adoption of financial technology.
A key observation is that, in the last 12 to 18 months, the use of artificial intelligence and machine learning in risk assessments and analytics has increased across a range of functions, including credit analytics, fraud and anti-money laundering detection, and regulatory compliance. Nevertheless, ongoing challenges discussed at the workshop include "black box" risk and explainability of machine learning models, including bias, ethics, transparency, and data privacy requirement, and data management. There was a recognition that, while artificial intelligence and machine learning models have characteristics that are common to other financial and regulatory models used by banks, artificial intelligence and machine learning models may amplify traditional model risks. One such subset of risks highlighted by participants are those related to data, including the quantity and quality of vast data sets, data access, and engagement with third parties that use or store data.
Additionally, discussions focused on the role of model risk management functions in overseeing artificial intelligence and machine learning validation and the challenges with having the right skill sets and expertise to address risks specific to artificial intelligence and machine learning. Supervisors also provided commentary on how they are considering the supervision and oversight of artificial intelligence and machine learning models. The SIG agreed that ongoing supervisory engagement with stakeholders and information sharing were beneficial and future outreach will be considered.
Related Link: Press Release
Keywords: International, Banking, Artificial Intelligence, Machine Learning, Workshop, Regtech, Fintech, Governance, Third-Party Service Providers, Big Data, BCBS
Previous ArticleIMF Publishes Reports and Technical Note Under FSAP with Thailand
The European Commission (EC) published a report summarizing responses to the targeted consultation on the supervisory convergence and the single rulebook in the European Union (EU).
The Office of the Superintendent of Financial Institutions (OSFI) published an update on the discussion paper that intended to engage federally regulated financial institutions and other interested stakeholders in a dialog with OSFI, to proactively enhance and align assurance expectations over key regulatory returns.
The European Central Bank (ECB) published its opinion on a proposal for a regulation on European green bonds, following a request from the European Parliament.
The Advisory Scientific Committee (ASC) of the European Systemic Risk Board (ESRB) published a report that explores the expected impact of digitalization on provision of financial and banking services, and proposes policy measures to address the risks stemming from digitalization.
The European Banking Authority (EBA) announced that the guidelines on the reporting and disclosure of exposures subject to measures COVID-relief measures shall continue to apply until further notice.
The Swedish Financial Supervisory Authority (FI) announced that the capital adequacy reporting as at December 31, 2021 must be done by February 11, 2022.
The Central Bank of the Philippines (BSP) issued communications covering developments related to online lending platforms, open finance framework and roadmap, and on the expected regulations in the area sustainable finance.
The Board of Governors of the Federal Reserve System (FED) published the final rule that amends Regulation I to reduce the quarterly reporting burden for member banks by automating the application process for adjusting their subscriptions to the Federal Reserve Bank capital stock, except in the context of mergers.
The European Banking Authority (EBA) published its assessment of risks through the quarterly Risk Dashboard and the results of the Autumn edition of the Risk Assessment Questionnaire (RAQ).
The Malta Financial Services Authority (MFSA) updated the guidelines on supervisory reporting requirements under the reporting framework 3.0.