Max Levchin’s Affirm Raises $275M to Make Loans
recode.net
recode.net
It's going to be interesting to see how these lenders show compliance with various aspects of the Fair Credit Reporting Act and Equal Credit Opportunity Act.
The latter, for instance, prohibits lenders from denying credit on the basis of race, color, religion, national origin, gender, marital status, etc. But it's possible some of the data points used by these lenders will turn out to be proxies for these attributes. There is already a lot of discussion around how lenders are using "big data" and the associated potential pitfalls[1][2].
[1] http://www.microfinancegateway.org/library/big-data-big-disa...
[2] https://www.aclu.org/blog/ftc-needs-make-sure-companies-aren...
Affirm chooses a rate based on its algorithm's prediction, and I believe worst case just offers standard FICO-based rates... because it has a slightly different business model, it has no incentive to ding customers with a $15 fee if they pay the third payment three days late.
Are any of these independent factors for greater (or lower) risk once other factors like income, education and conscientiousness are considered? If they aren't why do any lenders care and if they are then any lender is just going to use cruder proxies for these factors disadvantaging more people.
What I'd like to see is a disruption to banks to encourage people to save properly, by integrating proper budgeting and accounting into the bank account itself. I.e. walling money that is allocated for future expenses such as insurance, utilities, presents etc. On the other hand with no extortionate fees for going overdrawn. I'd love to see something like that.
Followup question: How would a company be able to come in and offer what you describe and offer users savings, and take a cut for themselves along the way, so that the users and the new company wins, while the incumbent banks lose?
Some banks offer something a little bit in this direction (at least in the UK and Australia). I have heard of banks with 'savings pots' and online saving planners.
For a bank it is probably good for them if you save. Eventually you will spend the money and in the mean time the saved money makes them money because (due to how the banking system works).
The way I can see this playing out is based on consumer demand. Banks have little in the way of genuine USP. I mean they all pretty much offer the same service and must compete on service, interest rates, fees, branding, reputation etc. So offering a way to help people save could be a good USP for the right kind of bank.
shame.
However Max and Affirm justify their business, there isn't an algo smart enough to only offer small credit to people who won't get in to trouble. In fact there is a huge incentive to lure people into using credit when they won't be able to handle it. Which is evidenced by almost any consumer credit business in history. Even if they say they won't charge late fees (for now), to play up their ethics, believe they are still going to be monetizing outstanding loans. Businesses like this (payday loan/ small credit / auto title loan / rent-to-own) typically sell their bad debt to recovery agencies and still turn a profit on the interaction. Not to mention Affirm will get a point or 2 from the merchant in all cases, I assume.
No surprise about the $275M though.
Also this seems to be more of a failing of the education system. Young people should learn the proper financial skills in school instead of relying on corporations to just help them out. All these loans are voluntary and help plenty of people who need a way to borrow.
We did this in the UK, Wonga.com/samedaycash firms everywhere and the government had to legislate to stop them exploiting the poor.
I think the people that are more likely to save are also the ones less likely to default on loans. Maybe it's just over-simplified thinking, but I think the reason Affirm works wonderfully is because they keep audience in mind. They pull in a ton of data points to assess the risk on investments, and I would love to see the percentage/demographics of people that get loans.
Of course mortgage is debt but it is backed by an asset, usually comes with an excellent interest rate that is very close to zero or negative in "real terms".
What I find really frustrating with most of these fintech companies is that they claim they use all kinds of data. But they don't really disclose whether this is used for 'underwriting' or 'fraud'. When it comes to underwriting there are specific FCRA guidelines on reason codes. For example, if they decline credit to a consumer because s/he did not type in their address fast enough, they need to tell them that. That would make for a good sound bite for the company.
Also, what if disabled people cannot type fast enough? That seriously touches on discrimination. Too bad CFPB is not going to care about these companies until they get to $10Bn in loan size.
> Also, is there data that shows that someone with a long commit streak is more creditworthy than someone without a Github profile?
That data doesn't exist; the precise job of this sort of correlation engine is to create it. In credit analysis, you start with a decent credit-worthiness model of all your customers—derived not from predictions, but from how people with a given feature-set did historically. Then you go looking for new feature datasets to incorporate into your model which decrease its RMSE at predicting split-subsets of your outcome data.
Github commit history could easily be one of these. I would guess it would be a good prediction of both average employment tenure, and of the Big 5 Conscientiousness personality trait.
But I don't have to be right—I just throw the feature-set into the engine, and it either finds signal in it and turns up its weighting in the model, or finds that it's noise and turns it down to zero.
what exactly is new here ?
Levchin is not young, so I guess his startup is DOA.
based on a person’s name, email, mobile number, birthday and the last four digits of his or her social security number
Onomancy, hotmailancy, astrology, and numerology, respectively. Ok I made up hotmailancy, but really. He just needed to add tiromancy and they could adopt Wallace and Grommet as their spokespersons.
Rationally speaking, how is his "trust us" remark any different from the US government NSA spying program's "trust us" remark?
You don't choose to do business with the NSA, you have no say in whether you consider their "product" worth the cost, and they cover up their own activities.
True. But that makes the business model more compelling. It doesn't negate the fact that it takes just one bad actor at Affirm to screw that trust up (just as easily as it takes just one bad actor at the NSA to screw their trust up).