By Alex Johnson
3 Fintech News Stories
#1: Making Credit Scores Obsolete
Tomo Credit – a fintech company focused on serving credit invisible customers – raised a $22 million Series B, with the goal of making credit scores obsolete:
Tomo is different from many other credit offerings out there in that it doesn’t rely on FICO scores to underwrite. Rather, it applies a “proprietary” underwriting algorithm (Tomo Score) to identify “high potential borrowers” without a credit score. The TomoCredit card requires no credit check, no deposit, 0% APR and no fees. The fintech offers cardholders credit limits up to $30,000 based on their cash flow. It makes its money only off of interchange fees charged to merchants, not off consumers directly.
Sounds risky? Well, it is.
But Kim maintains that the company’s default rate — at 0.11% — doesn’t reflect that risk. (For context, American Express reports a 2.5% default rate.)
Let’s add a little context.
Tomo’s credit card is unique. It requires consumers to connect an outside bank account (via Plaid or Finicity), which Tomo then utilizes for both the initial underwriting (by looking at cashflow history) and to facilitate autopay for customers’ balances. Payments are made every 7 days (rather than the typical 30) and customers are not allowed to carry a balance (if their linked bank account doesn’t have sufficient funds to pay the balance, the customer’s account is frozen). Repayment data is reported to all three bureaus, which helps build customers’ credit scores.
Why is this important?
First, it explains why Tomo’s default rate is 0.11%. Remember, Tomo requires autopay, and they don’t allow customers to revolve a balance. These are very customer-friendly product design choices, but comparing Tomo’s default rate to American Express’s is like comparing water and vodka.
Second, it casts this excerpt from the TechCrunch article in a different light:
The company plans to apply its new capital to diversifying its product offerings, such as offering auto loans and mortgages.
Given the large dollar amounts and long loan terms involved, the standard approach to underwriting auto loans and mortgages usually includes getting a look at the applicants’ credit files (or alternative data that provides similarly strong ‘willingness to pay’ signals). I have no idea how Tomo will successfully make the jump into auto and mortgage without this data.
#2: Ape Now, Pay Later (ANPL)
Two new BNPL services have been introduced for NFT investors.
The first is from a company called Super Mojo:
Super Mojo … announced the launch of its financing platform designed to make digital assets more accessible for the next wave of users. The platform facilitates point-of-sale financing to improve the NFT purchase experience and collateralized lending for improved post-sale liquidity. Supermojo’s initial focus will be on partnering with marketplaces and storefronts that serve the $25B NFT market.
And the second is being offered by Teller:
Decentralized finance (DeFi) lender Teller has introduced a buy now, pay later (BNPL) service for blue-chip non-fungible tokens (NFTs) like Bored Ape and others.
According to Bloomberg, intending buyers will pay a mandatory between 25% to 50% of the NFT value and the balance can be spread into installments.
Teller has named the service “Ape Now, Pay Later” and has built it on the Ethereum Layer 2 network, Polygon.
I don’t know, man. I feel like shouting THIS IS A REALLY BAD IDEA. And, also, IF YOU CAN’T AFFORD TO RECKLESSLY SPECULATE ON HIGHLY VOLATILE DIGITAL ART THEN YOU PROBABLY JUST SHOULDN’T DO IT. And maybe too THIS IS GOING TO BE AN INSANELY RISKY ASSET CLASS TO MAKE LOANS INTO, EVEN IF YOU RESTRICT IT TO SO-CALLED BLUE-CHIP NFTS.
But honestly, what’s the point?
#3: Fair Play
A fintech company focused on “fairness-as-a-service” raised $10M in Series A funding:
Launched in 2020 by CEO Kareem Saleh, FairPlay provides algorithmic fairness solutions that empower lenders to identify and mitigate bias in their credit models, increasing profitability and financial inclusion. The company’s AI fairness techniques reduce algorithmic bias for people of color, women and other historically disadvantaged groups to enhance fairness in financial services and other industries.
FairPlay offers two APIs. The first API provides Fairness Analysis, analyzing a lending model’s inputs, outputs and outcomes to identify if disparities exist and for which historically disadvantaged groups. The second API, Second Look, leverages Fairness Aware AI technologies to re-underwrite declined loan applications for borrowers from protected groups. The technology assesses whether applicants declined by the primary algorithm resemble ‘good’ borrowers in ways that weren’t previously considered. The result is that more applicants from underserved groups are responsibly approved for loans, reducing bias and increasing lenders’ profitability.
Seems like FairPlay is making a bet that three things will turn out to be true:
- The use of AI and machine learning in credit decisioning is going to increase sharply over the next decade or two.
- Regulators are going to continue applying a great deal of scrutiny to this practice and it will be worth it for financial institutions to invest in technology that can help them appease regulators’ concerns.
- FairPlay can help identify profitable applicants from underserved consumer segments that lenders should reconsider approving.
I absolutely buy #1 and #2. #3 seems a bit more challenging (depending on the details of how that second-look process is executed), but I’m certainly intrigued.
2 Fintech Content Recommendations
#1: How the Durbin Amendment Sparked Fintech Innovation (by Eric Glyman, Ramp, and Logan Bartlett & Emily Man, Redpoint Ventures) 📚
The fintech industry, as we know it today, wouldn’t exist without the Durbin Amendment. Neobanks’ reliance on Durbin-exempt interchange revenue is merely the most obvious and well-known example of this, but the ripples from this legislation stretch well beyond that.
This write up by Ramp and Redpoint Ventures is an excellent primer on Durbin and all of its intended and unintended effects.
#2: Crypto Primitives (by Ayokunle Omojola) 📚
This essay by Ayo Omojola is a wonderfully rational view into the potential value of crypto technology, which Ayo argues should be thought of not in terms of benefits, but rather in terms of features or primitives.
The section on DAOs was particularly interesting to me.