Financial

Hybrid Multi-Stage Adaptive Scoring

Problem

Scoring models have been used to define the risk and loyalty level of customers, consumers and new product buyers and specifically in the financial sector, credit scoring is a method of evaluating the credit risk of loan or credit applicants.
Nowadays, credit scoring plays a vital role in economic growth by improving easy and fast access to credit markets, lowering the price of credit and reducing the economic risks.
Credit scoring has gained more and more attention as the credit industry can benefit from improving cash flow, insuring credit collections and reducing possible risks.

Solution

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Traditional scoring methods require that a manual variable reduction/creation process based on trial and error is repeated for each update after model development.
Moreover, it is difficult to develop an adaptive credit scoring model based on the current linear methods due to their inherent constraints. Therefore, a dynamic modelling process using state-of-the-art hybrid techniques could be useful for the scoring tasks.
At Eris Innovation, firstly we used a multi-objective optimal variable selection in order to obtain the best subset of features with the minimum number of variables in that subset. Secondly we have developed a Hybrid Multi-Stage Adaptive Credit Scoring model applying some advanced metaheuristic classifiers.