Regulatory Alerts2021-07-15
Machine learning in risk models – Characteristics and supervisory priorities Consultation paper
BaFin issues this consultation paper to define the characteristics of machine learning methods in risk models and outline corresponding supervisory priorities for financial institutions. The document analyzes key ML traits such as hypothesis space complexity, training difficulty, adaptivity, and data basis to determine the intensity of regulatory scrutiny. It emphasizes that while existing technology-neutral regulations remain applicable, supervisors will focus on explainability, data quality, and the challenges posed by model changes and automation.
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