Senior Director, Principal, Risk Consultant
Dan is a senior director in the Moody's Analytics client management group. His primary responsibilities involve managing client relationships for large, complex implementation efforts. Prior to joining Moody’s, he had a long career in banking risk management, with leadership roles in RAROC, Basel II/III, and CCAR development efforts.
Dan has an MBA in finance from University of Chicago Booth School of Business and a BS in economics from the University of Chicago. He is a CFA.
This quantitative analysis of CCAR 2014 Severely Adverse scenarios, Moody's Analytics finds that the Federal Reserve Bank's (FRB's) and banks' own modeled estimates of capital ratios, revenue, net income, and loan credit losses are generally well aligned, although variations in all measures and across all banks are evident. In addition, the FRB's estimates are generally more conservative than those of the individual banks, reflecting differences in the FRB's industry-based models vs. the banks' portfolio specific models, treatment of missing or invalid data in the FRB's modeling approach, and assumptions about projected balance sheet volumes. The wide variation among bank modeled estimates and their overall alignment with FRB modeled estimates argues against banks targeting general industry benchmarks (such as average loss rates) and in favor of building models around their own business models and portfolio characteristics.
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.