Budde: Top credit variables hold 3-5% weight in ZestFinance models
Shawn Budde · Panel Discussion // NYC Data Business Meetup // Feb 2013 · Dec 5, 2013 · at 6:28
Shawn Budde explains how ZestFinance's machine learning models distribute impact across many variables compared to traditional credit scoring models.
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“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.”
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More from Shawn Budde
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.”
ZestFinance saw fraud drop 98% overnight after launching new model
“When we implemented in December, we saw fraud drop overnight by about 98% and we saw first payment failures drop by more than 40% you know, between December first and December second when we implemented the model.”
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.”
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.”
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.”
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…”