Success Story
Client Introduction
A well-known US-based commercial lending institution that provides leasing and financing solutions to equipment dealers, manufacturers, government agencies, and other businesses.
Problem Statement
The client used the Swiss Cheese Model for scoring new applications, sequentially pulling credit scores from multiple credit bureaus. However, this system had inherent challenges, as follows:
- The significant cost of implementing this multi-layered defense system, particularly the heavy reliance on one of the most expensive credit bureaus, made the process unsustainable.
- The oversimplified approach was insufficient for addressing complex lending scenarios, leading to potential risks and a false sense of security.
Solution Offered
Anaptyss used machine learning techniques and libraries, including Extreme Gradient Boosting (XGBoost), random forest, and regression analysis to address inefficiencies in the Swiss Cheese model. The solution optimized the effectiveness of each bureau model, eliminating redundancies and streamlining performance and accuracy.
Key Solution Delivered
- Reduced reliance on the most expensive credit bureau and streamlined use of other 3 rd party bureau models.
- Deployed featured engineering.
- Enhanced credit scoring with minimized gaps.
Business Outcomes
- 4US$ 400,000 in annualized cost savings
- Formation of a new, more efficient credit policy
- Reduced operational complexity
Want to learn more or need a solution?
Write to us: info@anaptyss.com