This site uses cookies to improve your experience. To help us insure we adhere to various privacy regulations, please select your country/region of residence. If you do not select a country, we will assume you are from the United States. Select your Cookie Settings or view our Privacy Policy and Terms of Use.
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Used for the proper function of the website
Used for monitoring website traffic and interactions
Cookie Settings
Cookies and similar technologies are used on this website for proper function of the website, for tracking performance analytics and for marketing purposes. We and some of our third-party providers may use cookie data for various purposes. Please review the cookie settings below and choose your preference.
Strictly Necessary: Used for the proper function of the website
Performance/Analytics: Used for monitoring website traffic and interactions
ƒFord Motor Credit Co. the financing arm of the vehicle manufacturer, announced Friday (Aug. 25) that it will implement machine learning credit approval models to determine if it will lend a consumer money as it goes after a segment of the market that doesn’t have a solid credit history.
But it occurred to them that their solution was useful outside of HR — and that many of the things that made someone a good hire of over time could also make them a good creditrisk over time, if the artificial intelligence (AI) model they were using to screen with were modified to that task.
It’s a town of about 4,000 people, so exposure to markets or investment banking or any of the careers in finance was not something that you really envisioned. And the whole concept of it was why don’t we take Liberal Arts majors, give them on-the-job training, give them exposure to a variety of different areas of banking and finance.
The challenge is unlike the S&P 500, hedge funds sit in a box that has underlying creditrisk from prime brokers. So the credit markets froze. RITHOLTZ: So hold the duration risk aside with those two, but just for an investor in treasuries, I know you’ve done the math before. How would you have done?
So, started examining opportunities in finance, real estate and insurance. RITHOLTZ: You know, what’s really interesting is everybody tends to think of Wall Street and investing and finance in terms of the investing side. A lot of people in finance have been saying it’s difficult to find people in this environment.
You graduate Emory University with a degree in finance. No, I’m — RITHOLTZ: You beat me by an hour, RIEDER: You know, I think, I would say to young people who come into the business, you know, why are you coming into finance? You know, whereas, parts of credit card, auto finance are more attractive.
And up until that moment in time, we didn’t spend a lot of time on creditrisk in mortgages. We didn’t really have to model creditrisk because that was, that risk was taken by the agencies. But in these private labels, you had the, the market was taking the creditrisk.
Jeffrey Sherman : Well, what it was was, so I, as I said, with applications, there’s many applications of math, and the usually obvious one is physics. Barry Ritholtz : It seems that some people are math people and some people are not. The, the math came easier. And I really hated physics, really. It’s so true.
We organize all of the trending information in your field so you don't have to. Join 39,000+ users and stay up to date on the latest articles your peers are reading.
You know about us, now we want to get to know you!
Let's personalize your content
Let's get even more personalized
We recognize your account from another site in our network, please click 'Send Email' below to continue with verifying your account and setting a password.
Let's personalize your content