2 résultats pour « irb »

Machine Learning and IRB Capital Requirements: Advantages, Risks, and Recommendations

This paper examines the use of #machinelearning methods in the context of #banks' #capitalrequirements, specifically the internal Ratings Based (#irb) approach. The authors discuss the advantages and risks of using machine learning in this domain, and provide recommendations related to #risk parameter estimations, #regulatory capital, the trade-off between performance and interpretability, international #banking competition, and #governance, #operationalrisk, and training.

A Stochastic Climate Model -- An approach to calibrate the Climate‑Extended Risk Model (CERM)

"These parameters can be calibrated using public data. This new approach means not only to evaluate climate risks without picking any specific scenario but also allows to fill the gap between current one year approach of regulatory and economic capital models and the necessarily long-term view of climate risks by designing a framework to evaluate the resulting credit loss on each step (typically yearly) of the transition path. This new approach could prove instrumental in the 2022 context of central banks weighing the pros and cons of a climate capital charge."