Machine learning methods
Credit institutions are increasingly using or examining the use of machine learning methods to speed up processes, reduce costs and make data available. However, the use of such methods is also accompanied by risks, which are subject to supervisory requirements. At the same time, the financial industry would like to see a clear communication of supervisory expectations regarding the use of machine learning.
Consultation 11/2021
The following joint consultation paper of BaFin and Deutsche Bundesbank deals with the concrete use of machine learning (ML) in risk models of Pillars I and II of the regulatory frameworks for banks and insurers. The paper is based on already published principles of BaFin and the Bundesbank for the use of Big Data and Artificial Intelligence (BDAI).
BaFin and the Deutsche Bundesbank are accepting comments by mail (see cover letter) until 30.09.2021.
Information provided by the Federal Financial Supervisory Authority
Policy Discussion Paper
The following document is intended to present the most important aspects to be considered for the supervisory approach to machine learning. For this purpose, possible supervisory expectations regarding, among other things, explainability, data requirements or risk management are also formulated. In addition, the discussion is to be moved from the term “artificial intelligence” to the concrete procedures and risks behind it.