Service overview


Basel is a set of recommendations on capital adequacy for international banks.

Basel has three components: minimal capital requirements, Supervision and market discipline.

Minimum capital requirements The capital-to-assets ratio is calculated using regulatory capital and risk-weighted assets. This ratio must be no lower than 8%. Tier 2 capital must not exceed 100% of Tier 1.

Supervision “This section is a discussion of principles of supervision, risk management, transparency and accountability to banking regulators developed by the Committee to control banking risks, including offers on, inter alia, treatment of interest risk in a portfolio, loan risk (stress-testing, default determination, residual and loan concentration risks), operational risk, growth of international communication and collaboration, security measures.”

Market discipline Market discipline is about information disclosure to control the former two components.

For the first component, minimal capital, we can use one of two approaches: standard, based on external asset ratings from international rating agencies, and internal rate-based (IRB), where the bank evaluates risks itself on a Basel methodology. The latter method can benefit from a good model.“Provided that certain minimal requirements are met and disclosures made, banks with regulators’ approval can use IRB to assess risk and capital adequacy themselves. Risk components include probability of default (PD), loss-given defaults (LGD), exposure at default (EAD) and effective maturation term (M).”

BSC’s RRAS comprises additional tools in order to create specialized reports and models of the second component - loan risk, market risk and more. This produces properly formatted estimates and forecasts to banking regulation standards.



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”.