Craig Peters heads a Model Risk Management team, where he promotes independent challenge processes that have been adapted for the unique nature of a software analytics firm. He designs and runs model risk management processes for his group, which develops and maintains Moody’s Analytics well-known credit risk models. He also manages a group of quantitative financial analysts performing implementation verification of these same models.
Econometric Modeling: Fully transparent econometric and statistical models to assess performance of geographies, financials and various asset classes.
Enterprise Risk: Business strategy to identify, assess, and prepare for any dangers to a firm's operations.
Portfolio Models: Models that enable portfolio managers to assess and optimize portfolio risk.
We explore constructing and applying Machine Learning Techniques that are both transparent and interpretable. Also discussed are leveraging a model-agnostic perspective and demystifying and socializing chosen ML risk models.
In this article, we review some of the most important model governance considerations, including how to approach new modeling needs, key differences between models for CECL and models for AIRB and DFAST, and the differing expectations for less complex banks.