This paper assesses the sensitivity of solvency stress testing results to the choice of credit risk variable and level of data aggregation at which the stress test is conducted. In practice, both choices are often determined by technical considerations, such as data availability. Using data for the Belgian banking system, we find that the impact of a stress test on banks' Tier 1 ratios can differ substantially depending on the credit risk variable and the level of data aggregation considered. If solvency stress tests are going to be used as a supervisory tool or to set regulatory capital requirements, there is a need to further harmonise their execution across institutions and supervisors in order to enhance comparability. This is certainly relevant in the context of the EUwide stress tests, where institutions often use different credit risk variables and levels of data aggregation to estimate the impact of the common methodology and macroeconomic scenario on their capital level while supervisors rely on different models to quality assure and validate banks' results. More generally, there is also a need to improve the availability and quality of the data to be used for stress testing purposes.
stress tests credit risk sensitivity analysis capital requirements modelling choices