Shawn Budde of ZestFinance shares real-world performance results from their December model launch to demonstrate the efficacy of their predictive modeling.
Disclosure
The CFPB approached ZestFinance offering regulatory protection for algorithmic underwriting
“We've, ah, we've actually been approached by the Consumer Financial Protection Bureau, ah, about, in essence, giving us kind of a waiver to say that, you know, we're gonna protect you from regulators who dispute this or don't like it.”
Assertion Not checkable as stated
Budde: Major lenders are not assembling advanced ML models for credit decisions
“Nobody is taking an SVM, ah, naive Bayesian, you know, A hidden mark off a random forest, and assembling those into a credit decision, as far as I know. We haven't come across them. I've talked to some of the biggest lenders.”
Assertion Not checkable as stated
Budde: ZestFinance does not scrape Facebook data for credit decisions
“Everybody kind of, everybody first off assumes that we're scraping Facebook. We're not.”
Insight
Budde: Top credit variables hold 3-5% weight in ZestFinance models
“The data that has the most impact Is the same data that has always had the most impact. It's just instead of being 10 or 15 or 20% of the equation, it's, you know, it's three to five percent of the equation.”
Assertion Not checkable as stated
Shawn Budde: Typical banks update credit models only once every 18 months
“A typical bank is gonna do a new model once every 18 months or so, ah, and they're gonna spend three to six months coding it up, you know, into a production system, and, ah, and validating that they didn't miss a decimal.”
Disclosure
Budde: ZestFinance operates as a direct lender, not a software vendor
“We're a lender. So we're, you know, we're not in the business, ah, primarily in the business of selling models or techniques. We're not a consulting company. We are actually making loans, you know, on our own portfolio, and that's where we believe the money is…”