Success Story
Client Introduction
A leading commercial lender based in the U.S., which offers leasing and financing solutions to equipment manufacturers, sellers, government institutions, and other organizations.
Problem Statement
The lender relied on credit risk scorecards of multiple third-party vendors to allow its predictive analytics model to assess prospective and existing borrowers. Additionally, the institution needed to ensure that all the credit risk scorecard models comply with the prevalent regulatory standards.
The requirements were as follows:
- An automated and reliable solution to validate the scorecard models of vendors, including FICO, Dun & Bradstreet, Experian, and PayNet
- A systematic and comprehensive record of the model design, development, and usage to facilitate better understanding, communication, and governance
Solution Offered
Anaptyss leveraged its deep domain expertise in credit risk management, including model validation and model documentation, and product engineering capabilities in intelligent automation solutions.
Key Solution Delivered
- Automated validation of risk models using a Python-based solution powered by machine learning
- Statistical and non-statistical methods for comprehensive and independent validation of vendorscorecards
- Comprehensive playbook with details of the process, methodology, rationale, and overall solution anatomy per the Enhanced Model Monitoring System (EMSS) guidelines
Business Outcomes
- Approx. 40% increase in the operational efficiency and reduced manual intervention
- Python codes for automated metric calculation
- 100% compliant credit risk models
- Reduced risks of penalties due to potential regulatory violations
Want to learn more or need a solution?
Write to us: info@anaptyss.com