Featured Product

    BaFin Issues Principles on Use of Big Data & Artificial Intelligence

    June 15, 2021

    BaFin published supervisory principles for the use of algorithms in the decision-making process of financial institutions. The principles are intended to promote responsible use of big data and artificial intelligence and facilitate control of the associated risks. The principles constitute preliminary ideas for minimum supervisory requirements related to the use of artificial intelligence and form the basis for discussions with various stakeholders. These principles can serve as guidance for entities under the supervision of BaFin. Additionally, BaFin and Bundesbank aim to publish a discussion paper by mid-July on the use of machine learning in Pillar 1 and Pillar 2 models; the focus will be on models that must be granted regulatory approval in the context of solvency supervision or models that are subject to prudential review.

    To formulate the principles as precisely as possible, an algorithm-based decision-making process has been broken down into two phases—development and application. The development phase examines how the algorithm is selected, calibrated, and validated. For instance, principles for the development phase relate to the relevant data strategy as well as documentation to ensure clarity for both internal and external parties. In the application phase, the results of an algorithm must be interpreted and included in the decision-making process. This can either be done automatically or by involving experts. A functioning mechanism comprising elements such as sufficient checks and feedback loops for the development phase must be established in all cases. Aside from these two phases, certain overarching principles are important for the creation and application of the algorithm and these include:

    • Clear management responsibility. Senior management must have sufficient technical expertise. Also, reporting lines and reporting formats must be structured to ensure that communication is risk-appropriate and geared to the specific requirements of the target audience, from the modeler right up to senior management. Moreover, the business-wide strategy for using algorithm-based decision-making processes should be reflected in the IT strategy. There must also be staff with the necessary technical knowledge in the independent control functions.
    • Appropriate risk and outsourcing management. Senior management is responsible for establishing a risk management system that has been adapted for the use of algorithm based decision-making processes. If applications are used by a service provider, senior management must also set up an effective outsourcing management system. Responsibility, reporting, and monitoring structures must be set out clearly within this context. Measures to minimize cyber-security risks should also be adapted if required and the complexity and data dependency of the algorithm must be considered.
    • Prevention of bias. Bias must be prevented to be able to reach business decisions that are not based on systematically distorted results, to rule out bias-based systematic discrimination of certain groups of customers, and to rule out any resulting reputational risks. This is a key principle since such biases may occur from the development of the process to its application. 
    • Ruling out of types of differentiation prohibited by law. In case of certain financial services, the law stipulates that certain characteristics may not be considered for differentiation purposes—that is, to calculate risk and prices. If conditions are systematically set out on the basis of such characteristics, there is a risk of discrimination. Such a risk also exists if these characteristics are replaced with an approximation. This would be associated with increased reputational risks and, in some cases, legal risks. In certain circumstances, BaFin might consider it necessary to take measures to address violations of statutory provisions. Companies should, therefore, establish (statistical) verification processes to rule out discrimination.

    These principles represent a milestone in the efforts of BaFin and Bundesbank to create legal and application certainty for the responsible use of big data and artificial intelligence in the financial sector. 

     

    Related Links

    Keywords: Europe, Germany, Banking, Big Data, Artificial Intelligence, Supervisory Principles, Cyber Risk, Algorithms, Outsourcing, Pillar 1, Pillar 2, Regtech, BaFin

    Related Articles
    News

    EBA Updates Filing Rules for Supervisory Reporting

    The European Banking Authority (EBA) published version 5.1 of the filing rules for supervisory reporting.

    October 19, 2021 WebPage Regulatory News
    News

    ECB Amends Guideline on Procedures for Collection of AnaCredit Data

    The European Central Bank (ECB) Guideline 2021/1829 on the procedures for the collection of granular credit and credit risk data has been published in the Official Journal of European Union.

    October 19, 2021 WebPage Regulatory News
    News

    ECB Amends Guideline on Procedures for Collection of AnaCredit Data

    The European Central Bank (ECB) Guideline 2021/1829 on the procedures for the collection of granular credit and credit risk data has been published in the Official Journal of European Union.

    October 19, 2021 WebPage Regulatory News
    News

    EBA Publishes Standards on Disclosure of Investment Policy Under IFR

    The European Banking Authority (EBA) published the final draft regulatory technical standards on disclosure of investment policy by investment firms, under the Investment Firms Regulation (IFR).

    October 19, 2021 WebPage Regulatory News
    News

    APRA Finalizes Guidance for New Prudential Standard on Remuneration

    The Australian Prudential Regulation Authority (APRA) published the prudential practice guide CPG 511 to assist banks, insurers, and superannuation licensees in meeting requirements of CPS 511, the new prudential standard on remuneration.

    October 18, 2021 WebPage Regulatory News
    News

    OCC Updated LIBOR Self-Assessment Tool for Banks

    The Office of the Comptroller of the Currency (OCC) published a bulletin that provides an updated self-assessment tool for banks to evaluate their preparedness for cessation of the London Interbank Offered Rate (LIBOR).

    October 18, 2021 WebPage Regulatory News
    News

    TCFD Updates Guidance for Financial Disclosures on Climate Risk

    The Financial Stability Board (FSB) published a report that examines the progress made toward disclosures aligned with recommendations of the Task Force on Climate-related Financial Disclosures (TCFD).

    October 14, 2021 WebPage Regulatory News
    News

    BCBS Report Examines Progress on Adoption of Basel III Framework

    The Basel Committee on Banking Supervision (BCBS) published the progress report on adoption of the Basel III regulatory framework in member jurisdictions.

    October 14, 2021 WebPage Regulatory News
    News

    ACPR Implements Updates Related to DPM Version 3.1

    The French Prudential Supervisory Authority (ACPR) has implemented, in its information system, updates linked to the Data Point Model (DPM) version 3.1.

    October 14, 2021 WebPage Regulatory News
    News

    EBA Note Examines Transition Risks of Benchmark Rates

    The European Banking Authority (EBA) published a thematic note that aims to identify and raise awareness of the transition risks of benchmark rates, as the London Interbank Offered Rate (LIBOR) and the Euro Overnight Index Average (EONIA) are close to being phased out.

    October 14, 2021 WebPage Regulatory News
    RESULTS 1 - 10 OF 7571