Service overview
Evaluation of credit portfolio model quality
BSC’ s unique experience developing forecasts for credit portfolios, access to industry data in many countries of the world and use of global best practices have resulted in a powerful model validation tool. The RRAS technology allows us to provide customers with:
- Model quality validation comparing with the best world practices
- Internal requirements and regulator standards compliance verification
- Creation of model testing algorithms and their deployment
BSC’s RRAS is a global leader among forecasting and stress-testing solutions, used by many retail credit banks. Regulating agencies and auditors are becoming stricter, models must be checkable and satisfy manager demands. Everything from model design to processing and criteria-finding is important. BSC’s new service gives customers all they need to pass audits and regulator scrutiny.
RRAS can validate models in the following ways:
- Evaluate completeness (fullness) of a model’s structure, its logic and fitness to purpose
- Check chosen time frames for the model and data
- Test the model’s accuracy
- View key assumptions
- Analyze sensitivity to scenario change
- Apply archived criteria and former forecasts from industry data
- Observe completeness and correctness of documents
- Develop continuous modeling
TRAINING CENTER
We offer courses on finance, credit, market and liquidity risks, pricing... To order e-mail us info@bsc-consult.com.
Risk management and international practice (16 hrs course)
Finance computing hands on (4 hrs. seminar)
Internal finance: bank department responsible for everything (4 hrs seminar)
PUBLICATIONS
The author presents the methods for studying credit portfolio behavior in the Modeling and Stress-Testing Credit Portfolio Behavior are partly based on so-called “dual time dynamics” method. This work suggests using dual time dynamics not for decomposing scalar values but for decomposing matrices. The author considers a credit portfolio as a process described by a first-order heterogeneous Markov chain. Starting from this premise, the author uses vintage analysis and the theorem of strong convergence of modified fixed-point algorithms to arrive at transition matrix decomposition. This method makes highly accurate forecasts of credit portfolios possible. Reserves can be estimated with excellent precision and relevant values for stress-testing obtained.
In his later article The Theory and practice of Retail Credit the author considers some successful practical applications of his methods described in the article “Credit portfolios behavior modelling and stress-test”.