Full case study available here.
More information on the software used in the study here.
A common challenge for banks is to develop consistent scenarios suitable for use as inputs to their regulatory or internal stress testing programmes. Regulators or senior managers may suggest scenarios involving certain variables but these rarely constitute a full of set of economic risk drivers for the bank’s loan book and other portfolios. The risk or the economics department of the bank is then faced with the task of “expanding the scenario”, i.e., coming up with plausible values for the key risk drivers not included in the original stress test specification.
To meet the needs of banks involved in stress testing, Risk Control has developed a data-driven framework for consistent scenario expansion. The approach utilises a statistical macroeconomic model to calculate conditional means of a set of variables given prescribed values for others. The procedure substantially reduces the need for users to utilise expert judgement, leading to greater objectivity and consistency. This note describes the approach in broad terms and provides a step-by-step case study of its application.
