Retooling for Credit Decisioning

In our last post, we examined a few opportunities within fraud detection and prevention that can benefit from AI. Today, we’re going to explore how AI can be applied to assessing creditworthiness in a post-COVID environment. Last year, we discussed how the ability to act and react quickly is crucial for the long-term success of consumer financing & lending institutions. Businesses that rely primarily on a traditional credit score to assess creditworthiness will struggle to act and react quickly in a manner that is profitable. Traditional credit scores are very good at identifying the most and least likely to repay. However, traditional credit scores aren’t objective measures like height, where someone who is 5’8” is always taller than someone who is 5’7”. Therefore, a customer with a lower traditional credit score may actually perform better than a customer with a higher one. And don’t forget, many consumers don’t have a credit score at all. Yet raising and lowering the score cutoff is usually the only lever that businesses have to control volume and mitigate risk. AI can be applied to better sort your applicants on ability and willingness to repay. 

Create infrastructure that supports orchestration and real-time decisioning.

Doing analysis on a sample of historical records offline is one thing. Being able to turn the insights of the analysis into action in real-time is another. Make sure you have the right infrastructure in place to handle AI-driven decision-making. 

Start with identifying patterns of fraud.

What percentage of your defaults were due to fraud? If you don’t know, we suggest starting with improving your fraud detection and prevention. The reason is that fraudsters often look good on paper (high credit score, good income, etc) and you don’t want their fake information to skew your analysis.

Leverage 3rd-Party data.

In general, the more data you have, the better your analysis. There is no one factor that predicts whether or not a customer will go into default. By integrating 1st-party data with 3rd-party data, you’ll be able to identify the most predictive combinations of factors. 

Through AI you can keep your acceptance rate the same while significantly reducing defaults or significantly increase your acceptance rate while maintaining your default rate. Either way, you’re making more profitable credit decisions without changing your marketing budget. In other words, AI can help you capitalize on the opportunities that you’re missing out on today.

Want to get up-and-running faster?
Contact us today to learn how you can take advantage of our FCRA- and HIPAA-compliant credit decisioning solution accelerator.

Enova Decisions

About

Enova Decisions is an analytics and decision management technology company that was formed in 2016 to help organizations make smarter, faster risk decisions about customers and consumers across the risk spectrum through big data, machine learning, and the cloud.