The answer is simple: Find the good borrowers which traditional credit scoring techniques oversees and rejects. And they do exist – traditional methods, such as logistic regression, has a hard time accurately classifying some populations, such as those with little credit history or people who have had past credit issues.
Traditional credit agencies usually categorize a applicant into a risk group between 1-10, which is a good indicator for many of the applicants. However each risk category will have some applicants who are misclassified – which should be classified in a higher or lower risk class. In sense, just because a person has a low credit score from a credit agencies it does not necessarily mean that he or she is a bad payer. And it goes goes to other way around as well, high scores doesn’t necessarily mean you are a good payer.
As can be seen in the picture above, an AI model will swap some of the borrowers to a higher risk class and some to the lower risk class. The end result is a credit decision model which helps you to either more approvals without increasing risk, or less risk with the same approval rate.
Evispot is a credit decision platform that helps you as a creditor to truly understand your customers. With the power of artificial intelligence, the platform reveals the complete picture of your customer behavior, enabling you to do more accurate credit decisions.
Evispot’s AI-platform help financiers to make use of more profitable AI credit models.
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