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Affirm Public S-1 Filing

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Re: Affirm Public S-1 Filing

#51

Post by cbhl »

slow_donkey wrote: post #31

Wonder if I'm the only one surprised by their actual revenue model. I had always assumed they made money off loan interest from consumers which they do, but it turns out over half of their 2020 revenue came from merchant fees instead. I just went through the Peloton flow to see for myself and indeed there's a 0% APR option for 3 years so it's clearly being paid for by Peloton. It also explains to me why people might…

I feel like the retailer side makes sense, even if you do 0% APR. The alternative to Affirm's merchant fee is a credit card merchant fee (say, 2.9%).

Affirm takes what would be a ~$600 or $2000 credit card transaction and turns it into a series of ACH payments. If (cost of ACH + cost of underwriting) < (cost of credit card merchant fee) then the merchant and affirm can split the difference.

Re: Affirm Public S-1 Filing

#54

Post by ec109685 »

slow_donkey wrote: post #31

Wonder if I'm the only one surprised by their actual revenue model. I had always assumed they made money off loan interest from consumers which they do, but it turns out over half of their 2020 revenue came from merchant fees instead. I just went through the Peloton flow to see for myself and indeed there's a 0% APR option for 3 years so it's clearly being paid for by Peloton. It also explains to me why people might…

Doesn’t this break down once interest rates ride higher then credit card rake?

Re: Affirm Public S-1 Filing

#55

Post by TheSpiceIsLife »

john_moscow wrote: post #44
kenrose wrote: post #26

Earlier quoted context omitted.

Your description sounds like the definition of financing. Yes, with financing there’s a trade off. In exchange for paying interest, you have the item that much sooner. Slightly tongue-in-cheek, but this is missing in your before example: Alice has to sit on the floor because she doesn’t have a chair. After 10 months of doing this, she has terrible posture and joint pain from sitting on the floor all the time. Despite…

>Yes, with financing there’s a trade off. In exchange for paying interest, you have the item that much sooner. Except then you want your next item and can't buy it because your credit limit is maxed out. So you have moved your "item queue" forward once or maybe twice, and now have one more rent to pay. You still have to wait for the next item, it's just instead of waiting for your savings to reach $100, you wait for…

> And the difference in life quality between America and Zimbabwe is because the previous generations of Americans possessed these skills and applied them wisely.

The grossly misrepresents what's happened in Zimbabwe.

I believe your intention was to suggest that by corrupting certain skills or values around finance or thriftiness or learning to build, etc etc, that the USA is on course for a significant decline in quality of life?

However, Zimbabwe's problems are rooted in a different, and much more pernicious, sort od corruption.

Re: Affirm Public S-1 Filing

#56

Post by tadkar »

Guest42 wrote: post #35
momokoko wrote: post #28

Earlier quoted context omitted.

> Consumer credit laws in the US so severely restrict what you can use for credit scoring purposes that better underwriting through data is basically a lost cause, absent some specific customer segment that has special credit situations. Can I inquire what your background is or where you found that information? Many companies supplement credit scores with additional data to make these types of decisions.

I’ve worked in credit risk modeling and it is rather strict the predictors that can be used and well documented. Data comes in from a variety of sources and it is favorable to be skilled in established models than to try something obscure that isn’t intuitive. The models have to work across different sets of time and the varying business processes that may have been in place. Fraud modeling is more flexible, but seem…

That is definitely changing in credit risk and underwriting as well. There are several companies like [1] applying deep neural nets to the credit risk problem. This on top of a lot of in house work in the big banks to “supplement” what is available on the open market

[1] https://zest.ai/

Re: Affirm Public S-1 Filing

#57

Post by nt2h9uh238h »

vira28 wrote: post #52

If merchants mostly pay the fee, how long before companies like Affirm becomes a commodity? (meaning won't the competition drive the fee down?)

It didn't happen to credit card companies in 60 years. They still charge merchants 2,9%. It's like a giant duopoly and fixed pricing. But in a real market, ofc you would be right. Maybe congress should look at VISA, Mastercard, AMEX instead.

Re: Affirm Public S-1 Filing

#58

Post by supernova87a »

Wow, kind of amazing that they're not losing tons of money through sales + marketing like every other IPO lately who lose 50% there. (they are losing money though). A little scary though, how much money they lose through bad credit write-offs, and what's the item about a huge loss for loan purchase commitments, both years?

Aside from those, they could be a really attractive business.

Re: Affirm Public S-1 Filing

#59

Post by [deleted] »

toomuchtodo wrote: post #39
herewhere wrote: post #38

Earlier quoted context omitted.

Recently, I went to Peloton dealership to order one bike. They offered 39 months 0% APR. I asked if they can give me some sort of cash discount. Because of lack of cash discount, and availability of 0% APR naturally I financed it. Perhaps, that's how Affirm is getting their business.

Quite the premium Peloton owners are paying in aggregate to subsidize that zero interest rate through merchant fees to Affirm. Peloton gets to immediately recognize the revenue of the sale (versus them carrying the debt themselves), and Affirm gets to show quality vintage from price insensitive prime borrowers.

[deleted]

Re: Affirm Public S-1 Filing

#60

Post by [deleted] »

tadkar wrote: post #56
Guest42 wrote: post #35

Earlier quoted context omitted.

I’ve worked in credit risk modeling and it is rather strict the predictors that can be used and well documented. Data comes in from a variety of sources and it is favorable to be skilled in established models than to try something obscure that isn’t intuitive. The models have to work across different sets of time and the varying business processes that may have been in place. Fraud modeling is more flexible, but seem…

That is definitely changing in credit risk and underwriting as well. There are several companies like [1] applying deep neural nets to the credit risk problem. This on top of a lot of in house work in the big banks to “supplement” what is available on the open market [1] https://zest.ai/

[deleted]
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