One of the main challenges that banks face in modeling operational risk is the instability of risk estimates caused by heavy-tailed and insufficient loss data. To address these issues, we propose a loss scaling method to combine a bank's internal loss data with external loss data of other banks....

We enhance the method of integrating scenarios proposed in Ergashev (J Financ Serv Res 41(3):145–161, 2012) into risk models. In particular, we provide additional theoretical insights of the method with focus on stress testing Value-at-Risk models. We extend the application of the method,...

Using supervisory operational loss data of the U.S. banking industry, we analyze correlations among operational losses within banks and across banks. We find evidence of relatively high correlations among tail losses of different operational risk types within banks. The median of these...

This study documents the association between the quality of risk management practices and operational loss realizations at large financial institutions in the United States. Using detailed supervisory data, we find that companies with weak risk management practices experience higher and more...

Operational risk models, such as the loss distribution approach, frequently use past internal losses to forecast operational loss exposure. However, the ability of past losses to predict exposure, particularly tail exposure, has not been thoroughly examined in the literature. In this paper, we...

The Federal Reserve's Comprehensive Capital Analysis and Review (CCAR) requires large bank holding companies (BHCs) to project losses under stress scenarios. In this paper, we propose multiple benchmarks for operational loss projections and document the industry distribution relative to these...

Operational risk is a substantial source of risk for US banks. Improving the performance of operational risk models' allows banks' management to make better risk decisions by better matching economic capital and risk appetite, and allows regulators to better understand the risk of banks. We show...