Featured Product

    FSB on Financial Stability Implications of AI and Machine Learning

    November 01, 2017

    FSB published a report examining the financial stability implications of the growing use of artificial intelligence (AI) and machine learning in financial services. The report draws on discussions with firms; academic research; public and private sector reports; and ongoing work at FSB member institutions.

    The first section of the report defines the key concepts of the report and offers context for the development of AI and machine learning for financial applications. The section describes supply and demand factors driving the adoption of these techniques in financial services. The third section describes four sets of use cases: customer-focused applications; operations-focused uses; trading and portfolio management; and regulatory compliance and supervision. The fourth section contains a micro-analysis of the effects of adoption on financial markets, institutions, and consumers. The fifth section offers a macro-analysis of effects on the financial system, with the final section concluding with an assessment of implications for financial stability. The FSB analysis reveals that the following potential benefits and risks for financial stability should be monitored, as the technology is adopted in the coming years and as more data becomes available:

    • The more efficient processing of information—for example in credit decisions, financial markets, insurance contracts and customer interactions—may contribute to a more efficient financial system. The applications of AI and machine learning by regulators and supervisors can help improve regulatory compliance and increase supervisory effectiveness.
    • Applications of AI and machine learning could result in new and unexpected forms of interconnectedness between financial markets and institutions, based on the use of previously unrelated data sources by various institutions.
    • Network effects and scalability of new technologies may in the future give rise to third-party dependencies. This could in turn lead to the emergence of new systemically important players that could fall outside the regulatory perimeter.
    • The lack of interpretability or auditability of AI and machine learning methods could become a macro-level risk. Similarly, a widespread use of opaque models may result in unintended consequences.
    • As with any new product or service, it will be important to assess uses of AI and machine learning in view of their risks, including adherence to relevant protocols on data privacy, conduct risks, and cybersecurity. Adequate testing and “training” of tools with unbiased data and feedback mechanisms is important to ensure applications do what they are intended to do.

     

    Related Link: FSB Report (PDF)

    Keywords: International, Banking, Insurance, Securities, Fintech, Regtech, Financial Stability, FSB

    Related Articles
    News

    APRA Publishes Approach to Regulating and Supervising GCRA Risks

    APRA published an information paper that sets out a more intensive regulatory approach to transform governance, culture, remuneration, and accountability (GCRA) practices across the prudentially regulated financial sector.

    November 19, 2019 WebPage Regulatory News
    News

    IAIS Publishes Application Paper on Recovery Planning

    IAIS published the final application paper on recovery planning, along with the resolution of comments on the draft application paper.

    November 18, 2019 WebPage Regulatory News
    News

    FSB Publishes Summary of November Meeting of RCG for MENA Region

    FSB published a summary of the November meeting of the Regional Consultative Group (RCG) for Middle East and North Africa (MENA).

    November 17, 2019 WebPage Regulatory News
    News

    EBA Single Rulebook Q&A: Second Update for November 2019

    EBA updated the Single Rulebook question and answer (Q&A) tool with answers to eight questions that relate to the Bank Resolution and Recovery Directive (BRRD) and the Capital Requirements Regulation and Directive (CRR and CRD).

    November 15, 2019 WebPage Regulatory News
    News

    FSI Examines Use of Red Team Testing to Enhance Cyber Resilience

    The Financial Stability Institute (FSI) of BIS published a paper that examines the contribution of red team testing frameworks toward enhancing cyber resilience.

    November 15, 2019 WebPage Regulatory News
    News

    FASB Delays Effective Dates for CECL, Leases, and Hedging Standards

    FASB issued two Accounting Standards Updates finalizing the delays in effective dates for standards on current expected credit losses (CECL), leases, hedging, and long-duration insurance contracts.

    November 15, 2019 WebPage Regulatory News
    News

    ESMA Updates Q&A on Securitization Regulation in November 2019

    ESMA updated questions and answers (Q&A) on the Securitization Regulation (Regulation 2017/2402).

    November 15, 2019 WebPage Regulatory News
    News

    HKMA Announces Finalization of Banking Liquidity Amendment Rules 2019

    HKMA issued a letter informing all authorized institutions that negative vetting of the Banking (Liquidity) (Amendment) Rules 2019 (BLAR) has now expired. Thus, the BLAR will now come into operation from January 01, 2020.

    November 15, 2019 WebPage Regulatory News
    News

    BCBS Consults on Revised Disclosures for Market Risk Framework

    BCBS launched a consultation on the revised disclosure requirements for the market risk framework for banks.

    November 14, 2019 WebPage Regulatory News
    News

    BCBS Consults on Disclosure Templates of Sovereign Exposures of Banks

    BCBS published a consultation on the voluntary disclosure templates related to sovereign exposures of banks.

    November 14, 2019 WebPage Regulatory News
    RESULTS 1 - 10 OF 4167