EconLab’s industrialized framework provides a complete stress testing solution. Incorporating state-of-the-art Bayesian techniques with modern ARDL modelling, our software is compliant with STAMP€ methodology, and offers an automated approach to stress testing and credit risk that allows you to better focus and allocate the bank’s resources in a single unified solution.
Our macroeconomic scenario generator will completely take care of internal scenario preparation. The modeller can specify a macroeconomic shock for given variables, and the generator will automatically prepare a scenario. Significant downturns and upturns for desired variables are modelled in a parametrized environment, which enables the modeller to acquire macroeconomic scenarios by setting shock amplitudes and transmission mechanisms. Generated scenarios are ready to be utilized by the scenario application tool.
Our modelling software employs BACE algorithms that are not – in contrast to many other common approaches – prone to overfitting due to application of modern econometric techniques. We offer modelling parameters as a modeller’s choice, but the ultimate model specification is based on multiple criteria with aim to deliver best performance.
Scenarios and market conditions change. It is therefore in the bank’s best interest to deliver reliable estimates and projections of key credit risk parameters. In our modelling software, the application of different scenario specifications is an automated task carried out completely in the background. Simply specify the scenario, and our software will generate projections of key credit risk parameters.
Understanding the risk drivers and sources of credit losses is crucial, especially in times with elevated uncertainty. In conjunction with automated projections of credit risk parameters for a particular scenario, our modelling software also offers partial macro analysis. By decomposing the projections, this provides a unique insight into credit losses.
Application of margin of conservatism is a complex task and should therefore not be prone to rework and model redevelopment. To further utilize available resources, our automated MoC calculation delivers MoC estimates based on different model specifications and scenarios. Projections’ confidence intervals are presented in an intuitive way, ready to be incorporated into any relevant documentation.
The ultimate goal of our solution is to provide a complete “hands-off” approach to stress testing. All features listed above are incorporated into a staging model that will calculate impairment charges based on given opening and long-run parameters. This operation includes calculations of loss rates, transitions, and long-run dynamics to deliver final estimates of economic losses and required impairment charges.
Internal and regulatory stress testing support. Development or ARDL-BACE PD and LGD stress testing models, macroeconomic scenario generation tool and staging module.
EBA EU-Wide Stress Test Exercise, included IFRS9 PD/LGD model review, development of benchmark PD/LGD/EAD models, IFRS9 Impairment calculations, data, analytics and documentation for regulatory review and industrialization of Stress Test/ICAAP framework