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 Publishes Final Regulatory Standards on STS Securitizations

    The European Banking Authority (EBA) published the final draft regulatory technical standards specifying and, where relevant, calibrating the minimum performance-related triggers for simple.

    September 20, 2022 WebPage Regulatory News
    News

    ECB Further Reviews Costs and Benefits Associated with IReF

    The European Central Bank (ECB) is undertaking the integrated reporting framework (IReF) project to integrate statistical requirements for banks into a standardized reporting framework that would be applicable across the euro area and adopted by authorities in other EU member states.

    September 15, 2022 WebPage Regulatory News
    News

    EBA Publishes Funding Plans Report, Receives EMAS Certification

    The European Banking Authority (EBA) has been awarded the top European Standard for its environmental performance under the European Eco-Management and Audit Scheme (EMAS).

    September 15, 2022 WebPage Regulatory News
    News

    MAS Launches SaaS Solution to Simplify Listed Entity ESG Disclosures

    The Monetary Authority of Singapore (MAS) set out the Financial Services Industry Transformation Map 2025 and, in collaboration with the SGX Group, launched ESGenome.

    September 15, 2022 WebPage Regulatory News
    News

    BCBS to Finalize Crypto Rules by End-2022; US to Propose Basel 3 Rules

    The Basel Committee on Banking Supervision met, shortly after a gathering of the Group of Central Bank Governors and Heads of Supervision (GHOS), the oversight body of BCBS.

    September 15, 2022 WebPage Regulatory News
    News

    IOSCO Welcomes Work on Sustainability-Related Corporate Reporting

    The International Organization of Securities Commissions (IOSCO) welcomed the work of the international audit and assurance standard setters—the International Auditing and Assurance Standards Board (IAASB)

    September 15, 2022 WebPage Regulatory News
    News

    BoE Allows One-Day Delay in Statistical Data Submissions by Banks

    The Bank of England (BoE) published a Statistical Notice (2022/18), which informs that due to the Bank Holiday granted for Her Majesty Queen Elizabeth II’s State Funeral on Monday September 19, 2022.

    September 14, 2022 WebPage Regulatory News
    News

    ACPR Amends Reporting Module Timelines Under EBA Framework 3.2

    The French Prudential Control and Resolution Authority (ACPR) announced that the European Banking Authority (EBA) has updated its filing rules and the implementation dates for certain modules of the EBA reporting framework 3.2.

    September 14, 2022 WebPage Regulatory News
    News

    ECB Paper Discusses Disclosure of Climate Risks by Credit Agencies

    The European Central Bank (ECB) published a paper that examines how credit rating agencies accepted by the Eurosystem, as part of the Eurosystem Credit Assessment Framework (ECAF)

    September 13, 2022 WebPage Regulatory News
    News

    APRA to Modernize Prudential Architecture, Reduces Liquidity Facility

    The Australian Prudential Regulation Authority (APRA) announced reduction in the aggregate Committed Liquidity Facility (CLF) for authorized deposit-taking entities to ~USD 33 billion on September 01, 2022.

    September 12, 2022 WebPage Regulatory News
    RESULTS 1 - 10 OF 8514