How to Lower Interest Rates for your SMB Embedded Finance Program

By Jared Shulman

August 17, 2022

How to Lower Interest Rates for your SMB Embedded Finance Program.

Affirm, along with what seems like thousands of its peers, unlocked the power of the bank statement for consumer credit underwriting. The powerful risk engines built by the $5b-$50bn startup – $10b at press time – augments traditional FICO analysis with the consumer’s bank transaction data to determine the risk of a Buy Now Pay Later (“BNPL”) loan.

This is a major market update from traditional credit card companies. It turns out, unsurprisingly, the now-archaic FICO score has historically been a fair (pun for all Fair Isaac Co. devotees) but certainly unimpressive predictor of consumer credit worthiness. The bank statement can detail spending patterns, verify self-reported income (something only ~4% of traditional lenders actually do), and pull out real-time analysis which Fair and Isaac could never imagine. This directly translates into a more accurate picture of a borrower’s ability to payback and, as a result, is at least partly to thank for the considerably lower interest rates charged by BNPL compared to credit cards.

Small business underwriters have taken note. We talk about the Big A.S.S lenders – Amazon, Shopify and Square for those new to our parlance – who use platform data to more accurately predict their customers’ business health. MCA lenders turned fintechs (read: cough cough) hope for the same luck by tapping publicly available APIs to emulate a similar effect. Sadly, it would appear that many of the early adopters in the embedded SMB lending (“EmFi”) space are failing to follow suit. Instead, it seems many of these EmFis rely only on bank statements to do their underwriting dirty work – ignoring the crown jewel of the partner platform data – at the expense of their SMB customers. 

The explicit cost is in the form of higher interest rates to SMB borrowers. Good underwriters, much like good farmers, learn to separate the wheat from the chaff. The most effective ones can do it threshing machine style. When chaff gets mixed with the wheat at the weighing station, the farmer’s yield is dinged. When a lender includes a few sub-par borrowers in their pool of quality companies, the analogy holds. Bad underwriters must charge all of their borrowers a higher rate to make up for it.

EmFi’s that do not use platform data are at risk of quickly being replaced by better tech.

As powerful as the bank statement has become in the consumer lending industry, its magnitude is limited in SMB lending – especially for larger credit transactions. Platform data – data generated by an ERP, Marketplace, or other SaaS vendor platform in which the EmFi is embedded – is a trove of insights that are completely missed by the bank statement. 

Client payment data, for example, can be used to create important factors around sales data and customer concentration – typically derived from a bank statement. Missed or delayed client payments, however, are arguably even more significant in credit assessment – something that is only discovered by poring through platform data. Some (well, at least us) argue the value of such platform data and its ability to predict future revenue, operator behavior and even fraud makes for a stronger collateral than land or equipment (which many “asset light businesses” don’t exactly have)!

The good EmFi businesses have built underwriting systems to capture both traditional underwriting data and platform data to enhance their credit decisioning. The great ones use it to make instant decisions and fund customers with honest and fair rates. The best ones write about and share how they do it


We hope to see more embedded lending programs truly capture the value of platform data to bring financing fees down across the small and mid-sized business ecosystem. Find out how Lendica easily connects, collects, and assesses partner platform data for your embedded finance program to lower rates and increase conversion for your SMB customers.