Innovation in Lending

How AI Can Help Lenders Weather The Storm

Zest AI team

April 15, 2020

As lenders consider how to manage the emerging economic crisis from the COVID-19 pandemic, many are looking for better data. They’re going to have to re-evaluate existing loans to mitigate potential losses and, in the future, become more selective about how they extend credit. Having the best tools at hand to climb out of the current hole is important not just now but also for the future. This post dives into how artificial intelligence and machine learning help limit current losses while enhancing future profitability.

If you prefer video, check out our recent webinar with Consumer Bankers Association (CBA): Climbing Through Crisis: How AI Can Help Your Lending Business Respond >

Better Predictions

Using machine learning helps you make better use of the data you already have. In a traditional model, you might have 30 or 40 data features. With machine learning, you can collect and fully incorporate all available data. Instead of being confined to 30-40 variables, machine learning can expand a feature set because the models are more sophisticated which help paint a better picture of your borrowers. This can include information about payment histories for rent, utilities, and cell phones. More data and advanced mathematical modeling lead to better predictions.

Machine learning can track non-linear behavior data, such as the number of inquiries a consumer makes. Extremely low numbers of inquiries can represent a risky borrower because that person may have a limited history and limited performance data, such as an 18-year-old who is just beginning to build a credit history. As the number of inquiries grows the risk typically decreases as there is more data available to paint a more accurate picture of an applicant. Sometimes, the number of inquiries can reach an amount — perhaps 40 or 50 — that actually raises red flags about a person’s risk profile. This type of non-linear behavior can’t be captured by traditional modeling techniques.

Improvements in predictability can impact performance. The better predictions generated by machine learning can reduce net charge-offs 20% to 30% for new portfolios when holding an approval rate constant, or growth of about 10% to 20% when holding the charge-off rate constant.

Advanced Monitoring

Predictions can be lost if you don’t have advanced monitoring. Model monitoring ensures accuracy and validity, to help you stay the course. We are seeing the importance of model monitoring with the current economic volatility from COVID-19. It’s also important because of the sheer amount of data machine learning models assess makes it possible for some interactions to go unnoticed. Machine learning can test models as they are being trained to see whether their signals change from the training period to when they are put into use. This ensures stability and reliability.

Machine learning can quickly alert you to changing behavior. In early March, one client got an alert just around the time the impact of COVID-19 first began to become widespread. In the past few weeks one group, whose incomes had remained stable, had begun to accumulate more debt. This could represent an uptick in the percentage of available credit being used, presenting significant risk exposure to a given lender. This type of rapid signaling can only really be found with machine learning. We shared this insight quickly with the client, giving them time to take action.

Fast Response and Documentation

In times of economic uncertainty, there are bound to be changes in your borrowers which means that you may need to create a new model.The traditional way of creating a new model is time consuming and at times like this, you can’t afford to wait a year.

That’s where machine learning can help. It turns a year or more of work down to weeks. With more data points, there is less impact per feature. And with automated documentation, it enables your teams to get to market faster.

Zest machine learning models are compliant with existing banking regulations. When you make credit decisions using Zest’s technology, they are delivered in a way that’s fully explainable. The machine learning technology also delivers automated documentation that is compliant with applicable banking regulations. While AI and machine learning can’t stop the volatility we’re about to experience, it can help to mitigate its impact on lenders portfolios.

Watch our recent webinar with Consumer Bankers Association Climbing Through Crisis: How AI Can Help Your Lending Business Respond.

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