Reject Inference Methods

It can be very dangerous to base lending decisions solely on the behaviors and characteristics of accepted borrowers, or clients. In fact, poor lending rules can be exacerbated and millions of dollars lost if lending institutions do not properly and accurately develop their lending policies, and “acceptance” guidelines. Developing a solid and sound model (or scorecard) using a reject inference can substantially increase the size, and quality of a customer base or portfolio.

In this article, we will look at the use and development of reject inferences for the purpose of raising profits and increasing market share.

1. What is Reject Inference

A Reject Interference is a method for improving the quality of a scorecard based on the use of data contained in rejected loan applications.

When developing a scorecard, we normally use information on those borrowers who have previously been granted a loan. However, the number of potential customers is significantly higher and a correctly developed scorecard must be able to perform as expected in the context of the entire population of potential customers.

The behavior of new types of borrowers can significantly differ from the behavior of the borrowers included in our credit portfolio.

To improve our knowledge of potential borrowers, we can use information on those customers who applied for and were refused a loan.

To develop a scorecard, we need to identify each borrower either as a "good" one or a "bad" one. However, there is no information available for rejected loan applications. We cannot tell for sure, to which group a borrower would have belonged, had he/she been granted a loan. The Reject Interference  methods are intended to provide the most correct way to perform the Good-Bad  identification of rejected applications in order to include them into the development set, based on which we can build a scorecard. Based on this new scorecard and the “RI” approach, we can then determine what the impact of our policies and decisions truly are, and ultimately make adjustments and corrections as we attempt to grow our business.

2. Simple Augmentation