Featured Product

    ACPR Seeks Views on Governance of Artificial Intelligence in Finance

    July 09, 2020

    ACPR published a discussion paper on the governance of artificial intelligence in finance. In this paper, ACPR has proposed four principles for evaluating artificial intelligence algorithms and tools—namely, data management, performance, stability, and explainability. ACPR also recommends the governance concerns that need to be taken into account, as early as the design phase of an algorithm. These concerns involve the integration of artificial intelligence into traditional business processes; the impact of this integration on internal controls; the relevance of outsourcing (partially or fully) the design or maintenance phases; and the internal and external audit functions. The comment period for this discussion paper ends on September 04, 2020.

    The governance of artificial intelligence algorithms requires careful consideration of the validation of each decision-making process. The regulatory compliance and the performance objectives of these algorithms are only achievable through a certain level of explainability and traceability. In the discussion paper, ACPR recommends focus on the following aspects of governance concerns:

    • Integration of artificial intelligence into business processes. This involves ascertaining whether the artificial intelligence component fulfills a critical function, by dint of its operational role or of the associated compliance risk and whether the engineering process follows a well-defined methodology throughout the machine learning lifecycle (from algorithmic design to monitoring in production), in the sense of reproducibility, quality assurance, architectural design, auditability, and automation.
    • Human-algorithm interactions. Those can require a particular kind of explainability, intended either for internal operators who need to confirm or reject an algorithm’s output, or for customers who are entitled to understand the decisions impacting them or the commercial offers made to them. Besides, processes involving artificial intelligence often leave room for human intervention, which is beneficial or even necessary, but also bears new risks. Such new risks include the introduction of biases into the explanation of an 4 algorithm’s output, or a stronger feeling of engaging one’s responsibility when contradicting the algorithm than when confirming its decisions.
    • Security and outsourcing. Machine learning models are exposed to new kinds of attacks. Furthermore, strategies such as development outsourcing, skills outsourcing, and external hosting should undergo careful risk assessment. More generally, third-party risks should be evaluated.
    • Initial and continuous validation process. This process must often be re-examined when designing an artificial intelligence algorithm intended for augmenting or altering an existing process. For instance, the governance framework applicable to a business line may in some cases be maintained, while, in other cases, it will have to be updated before putting the artificial intelligence component into production. Continuous validation process. The continuous monitoring of machine learning algorithm, for instance, requires technical expertise and machine-learning-specific tools to ensure the aforementioned principles are followed over time (appropriate data management, predictive accuracy, stability, and availability of valid explanations).
    • Audit. For internal and external audits of artificial-intelligence-based systems in finance, exploratory work led by the ACPR suggests adopting a dual approach. The first facet combines analysis of the source code and data with methods for documenting artificial intelligence algorithms, predictive, models and datasets. The second facet leverages methods providing explanation for an individual decision or for the overall behavior of the algorithm; it also relies on two techniques for testing an algorithm as a black box: challenger models (to compare against the model under test) and benchmarking datasets, both curated by the auditor.  

     

    Related Links

    Comment Due Date: September 04, 2020

    Keywords: Europe, France, Banking, Insurance, Governance, Artificial Intelligence, Fintech, Machine Learning, Regtech, Outsourcing Arrangements, ACPR

    Related Articles
    News

    ESAs Issue Multiple Regulatory Updates for Financial Sector Entities

    The three European Supervisory Authorities (ESAs) issued a letter to inform about delay in the Sustainable Finance Disclosure Regulation (SFDR) mandate, along with a Call for Evidence on greenwashing practices.

    November 15, 2022 WebPage Regulatory News
    News

    ISSB Makes Announcements at COP27; IASB to Propose IFRS 9 Amendments

    The International Sustainability Standards Board (ISSB) of the IFRS Foundations made several announcements at COP27 and with respect to its work on the sustainability standards.

    November 10, 2022 WebPage Regulatory News
    News

    IOSCO Prioritizes Green Disclosures, Greenwashing, and Carbon Markets

    The International Organization for Securities Commissions (IOSCO), at COP27, outlined the regulatory priorities for sustainability disclosures, mitigation of greenwashing, and promotion of integrity in carbon markets.

    November 09, 2022 WebPage Regulatory News
    News

    EBA Finalizes Methodology for Stress Tests, Issues Other Updates

    The European Banking Authority (EBA) issued a statement in the context of COP27, clarified the operationalization of intermediate EU parent undertakings (IPUs) of third-country groups

    November 09, 2022 WebPage Regulatory News
    News

    OSFI Sets Out Work Priorities and Reporting Updates for Banks

    The Office of the Superintendent of Financial Institutions (OSFI) published an annual report on its activities, a report on forward-looking work.

    November 07, 2022 WebPage Regulatory News
    News

    APRA Finalizes Changes to Capital Framework, Issues Other Updates

    The Australian Prudential Regulation Authority (APRA) finalized amendments to the capital framework, announced a review of the prudential framework for groups.

    November 03, 2022 WebPage Regulatory News
    News

    BIS Hub and Central Banks Conduct CBDC and DeFI Pilots

    The Bank for International Settlements (BIS) Innovation Hubs and several central banks are working together on various central bank digital currency (CBDC) pilots.

    November 03, 2022 WebPage Regulatory News
    News

    ECB Sets Deadline for Banks to Meet Its Climate Risk Expectations

    The European Central Bank (ECB) published the results of its thematic review, which shows that banks are still far from adequately managing climate and environmental risks.

    November 02, 2022 WebPage Regulatory News
    News

    ESAs, ECB, & EC Issue Multiple Regulatory Updates for Financial Sector

    Among its recent publications, the European Banking Authority (EBA) published the final standards and guidelines on interest rate risk arising from non-trading book activities (IRRBB)

    October 31, 2022 WebPage Regulatory News
    News

    EC Adopts Final Rules Under CRR, BRRD, and Crowdfunding Regulation

    The European Commission (EC) recently adopted regulations with respect to the calculation of own funds requirements for market risk, the prudential treatment of global systemically important institutions (G-SIIs)

    October 26, 2022 WebPage Regulatory News
    RESULTS 1 - 10 OF 8582