"As a team we have been very impressed with the speed of delivery and accuracy."  

Justus Ortlepp, Business Analyst 

Rand Merchant Bank assesses Credit Risks with help of the Credit Risk Rating Module

Credit Risk Rating according to IRB Approach

Rand Merchant Bank (RMB), a division of FirstRand Bank Limited, is a leading African investment bank and part of one of the largest financial services groups in Africa. In 2007, RMB implemented the IRB approach and therefore needed to meet these strict operational rules. The risk models like probability of default or loss estimates should be provided in the calculation of capital requirements. But despite the outstanding quality of RMB’s rating models, the rating models did not meet the requirements of up-to-date auditing as far as processes were concerned. A software solution should be found that not only fulfills these tasks but is also flexibly adaptable by business analysts and can be used by credit analysts via a web-based platform.

ACTICO's Credit Risk Management Platform

Rand Merchant Bank trusted in ACTICO's Credit Risk Management Platform to face the challenge. The underlying business rules technology ACTICO Rules offers a unique intuitive approach for modeling rules. RMB started with the most important ratings for the evaluation of credit risks: the probability of default (PD) and the loss given default (LGD). To represent these rating services, 6,000 rules had to be defined. Business analysts are able to define, test and document rule models via the graphical user interface. When rule models are released credit analysts use the web-based work environment for credit ratings. The final credit risk metric includes hard facts such as the ratings of external rating agencies as well as soft facts, e.g. the evaluation of a company by the bank‘s analyst. The bank's results are provided as encapsulated services in a service-oriented architecture for various applications.

Achieved Project Targets

Implementation of a centralized and robust rating system

Deployment of all bank-internal probability of default and loss given default rating models

Auditable data repository that stores historical output data for portfolio modeling, stress testing and scenario analysis

Seamless integration into existing system and process landscape 


"The implementation of the rating models in a robust technical environment has had a very positive impact on the way credit rating is done, both from a user perspective and also from a model development perspective. The system has also made it possible to meet our regulatory obligations at an unprecedented level."

Justus Ortlepp, Business Analyst, Rand Merchant Bank


Read our Success Story to learn more about software-based credit risk rating at RMB.