How Artificial Intelligence (AI) Improves Credit Underwriting
How can you as a creditor increase your lending portfolio without adding risk?
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.
By utilizing the power of AI we can get a complete picture of your applicants. Using more data, and more importantly, by understanding and capturing the interactions between the data is it possible to understand who will pay back and not. Resulting in more accurate credit decisions for you.
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’s AI-platform help financiers to make use of more profitable AI credit models. If you are ready to take the next step contact us at email@example.com