How AI Is Changing Lending (Podcast)
If AI is good enough to power self-driving cars, isn't it good enough to make credit risk decisions? What are the challenges lenders face using AI and machine learning models today…
If AI is good enough to power self-driving cars, isn't it good enough to make credit risk decisions? What are the challenges lenders face using AI and machine learning models today?
In this podcast for Lend Academy, FICO Blog author Dr. Scott Zoldi talks about his role as FICO's Chief Analytics Officer, the company's AI innovations and how they are being applied in credit risk, fraud management and more.
Listen to the podcast:
"I'm excited that machine learning and AI is the rage again, I think that's a really positive thing because it's a tremendously interesting set of technology," Scott says in the podcast. "What I worry about is it takes a lot of care to properly productionize and operationalize AI. From making sure that models aren't overtrained, to making sure that you have the proper amount and degrees of freedom, that you really thought about the data you bring into the machine learning models so it doesn’t learn relationships that might cause bias or might cause the model to not perform in predictable, reliable ways.
"At FICO we have a lot of experience with this and we treat it with a lot of care and we have a lot of governance around these models in terms of how to develop them. We encourage our customers to apply governance once these models are installed. A lot of people look to machine learning as being kind of a savior for all these investments they've made collecting data over these years and, one of the worst things we can do is just blindly apply these technologies."
Scott discusses:
- Why his background in theoretical physics was perfect for studying fraud and credit risk.
- The importance of being able to explain how a credit model works.
- How advanced machine learning models can be explained to regulators.
- What Scott thinks about the sudden embrace of artificial intelligence in the last couple of years.
- What he worries about with so many new companies coming into the AI fray.
- How Scott views alternative data and using new data sources.
- His thoughts on disparate impact and the use of alternative data.
For more information, visit the Lend Academy page on this podcast. This episode of the Lend Academy Podcast was sponsored by Wunder Capital.
You can follow Scott on Twitter @ScottZoldi.
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<p>FICO’s latest research on <a href="http://www.fico.com/en/blogs/risk-compliance/us-credit-quality-rising-the-beat-goes-on/" target="_blank">national FICO® Score distribution</a> shows that US credit quality continues to trend upwards, with an increasing number of consumers scoring in the highest scores ranges. Given that, we decided it was time to refresh our study on “<a href="http://www.fico.com/en/blogs/risk-compliance/infographic-what-does-a-high-credit-scorer-look-like/" target="_blank">FICO® Score high achievers</a>,” where we examine the credit behavioural profiles of consumers with higher credit scores.</p> <p>As expected, our latest study showed that older people generally have higher scores, as has been the case in our <a href="http://www.fico.com/en/blogs/risk-compliance/age-before-beauty-credit-worthiness-before-youth/" target="_blank">past research</a>. 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I further broke this down by looking at the characteristics of the youngest 15% in each group, which occurs at age 29 for the 750-799 group and 43 for the 800-850. We used FICO<strong>®</strong> Score 9 for our analysis, and examined typical variables of the categories that go into the make-up of the score.</p> <p><a href="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png"><img class="alignnone size-full wp-image-29367" src="http://www.fico.com/en/blogs/wp-content/uploads/2016/10/FICO-Score-High-Achiever-table.png" alt="fico-score-high-achiever-table" width="715" height="747" /></a></p> <p>Since there’s a lot to dissect in this chart, I’ll highlight a few findings that struck me: <ul> <li><strong>Credit history.</strong> Higher scores are undoubtedly associated with a longer time on file. What’s striking is the higher average time on file for the 800+ group, both overall and for revolving accounts (the most common trade line). Clearly, it helps to start credit use early in life – but that’s not the sole determining factor for high scoring. The younger cohorts in both the 800+ and 750-799 groups have time on file medians significantly less than their older counterparts.</li> <li><strong>New credit.</strong> High credit scorers do, in fact, pursue new credit. We see little variation in months since last trade line opening and last inquiry among all groups observed.</li> <li><strong>Pay on time.</strong> As you might expect, the further in the past the delinquency, the higher the score – and that’s <u>if</u> a delinquency ever happened. 95% of the 800+ people and 72% of the 750-799 group have never been delinquent, which is a striking contrast to the 57% for the total population. The percentages for the younger groups are even higher, especially so for the 750-799ers. Collection items are also scarce for these high scorers. While 23% of the national population have collection items greater than $99, the figures are only 0.5% for the 800+ group and 3% for the 750-799 group. It is clear that, in conjunction with starting a credit file early, paying on time is a key trait of the FICO® Score high achiever.</li> <li><strong>Balance and utilization.</strong> Finally, we look at how credit is being used, focusing on revolving product use. (Since most people only have one mortgage or one auto loan, variation in instalment product figures is minimal and driven by payment history, which is near perfect for high scorers, as we’ve seen.) FICO® Score high achievers tend to have more open revolving accounts. While the % active trades and utilization are generally lower, by no means do high scorers avoid the use of credit products. What drives the difference here is the amount of <u>available</u> revolving credit utilized. 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It ain’t rocket science!</p>
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