Case Study: Implementation of Credit Risk Engine
Client
Wholesale Bank based in Bahrain having exposures across carious asset classes such as Sovereign, Banks
and Corporates
Broad Scope
The Bank wanted to implement Credit Risk Rating Model within their credit approval process for existing
& new customers related to Banking and Corporate exposures asset class. The scope included development
of Master Rating Scale, development of Financial Institutions & Corporate Rating Models, Installation of
models on Credit Risk Engine under RiskCube platform and configuration of approval process workflow and
comprehensive MIS with rating reports, complete history of customer data and their internal / external
risk ratings, rating migrations, process monitoring reports, rating review calendars, rating wise
portfolio and industry reports; all these at customer & portfolio level covering all asset classes.
Our Approach & Solution
To achieve project objectives we have developed two separate Financial Institutions and Corporate Credit
Risk Rating Models for the Bank. The Rating Models were developed in compliance with guidelines
mentioned in Basel II accord and related developments. Implementation of these models was done by
configuring these models in Credit Risk Engine product module within RiskCube platform. All supporting
information like Master Rating Scale, Adjustments, model and judgement over-rides, User defined customer
and model applicability criteria was configured in Credit Risk Engine.
During start of the initiative, we developed a master rating scale for the Bank. As next step, FI and
Corporate Rating Models were developed covering variety of quantitative (financial) & qualitative
factors covering business, financial, industry, company and management specific factors. These models
were thoroughly tested and calibrated in coordination with expert Business and Risk Teams and using
customer data from existing portfolio.
Our flexible product platform ensured all credit risk evaluation rules and parameters were successfully
configured and parametrized through easy-to-navigate front end screens. We were able to achieve complete
and accurate automation of the credit risk evaluation and rating process to enhance efficiency and
effectiveness of existing credit approval process. The Bank was able to automate and successfully
capture all input, intermediate and final data fields for all customers, including historical data and
archival process, leading to creation of critical and risk information for Risk Data Mart.
A thorough UAT was conducted UAT was successfully conducted by Business, Credit and Risk Management
teams Risk Management department covering all process, accuracy of output and MIS and for consistency
and robustness of the platform. The results were fully reconciled to the General Ledger and Balance
sheet information. The project was then successfully moved to production environment for day to day use
and conduct of Credit Risk Ratings.
Business benefits
Significant business benefits were achieved post project implementation. Apart from implementing global
benchmark best practices, the Bank was successful in complying with latest Basel guidelines related
Rating model design, methodology, processes and operating environment From a rudimentary basic
judgmental process for credit evaluation, the Bank successfully moved to a rating model based credit
decision making process in compliance with global benchmark and in line with leading global and regional
institutions.
Additionally, Credit Risk Engine within RiskCube platform has helped the Bank successfully enhance its
Risk Data Mart which has become the repository of critical customer and deal level risk data for conduct
of future risk analytics and model validation exercise.
