Fintech Stratyfy raised $10 million with this pitch deck
- Stratyfy uses artificial intelligence to help lenders provide more credit to underbanked communities.
- The startup raised $10 million on March 29 from Truist Ventures, Zeal Capital Partners and others.
- Here’s the 13-page pitch deck that Stratyfy used to raise the so-called “institutional seed.”
Laura Kornhauser, a former CEO of JPMorgan Chase, was surprised when she received the adverse action notice informing her that she had been denied credit.
Kornhauser had been invited to apply for college credits several times while completing her MBA at Columbia Business School in the fall of 2016. But because she was a full-time student, she didn’t have much current income.
She called the 1-800 number on the back of the notice, and after providing additional information to the representative, Kornhauser got the lender to approve her.
“It really made me recognize that there are these huge pockets of our population that are just basically rejected by everybody,” Kornhauser told Insider.
People with lower Fico scores, those who do not have a long history of credit in the US, or workers who do not receive a traditional W-2 from their employers all fall into a bucket that is not “effectively seen” by the way many lenders evaluate potential borrowers, she added.
The experience led Kornhauser to start a business that helps lenders understand “real risk versus perceived risk” for individuals and small businesses, she said. A few months later, Kornhauser and her co-founder, Dmitry Lesnik, founded Stratyfy.
On March 29, the startup raised $10 million in a so-called “institutional seed,” which falls between a traditional seed and Series A, Kornhauser said. The round was led by Truist Ventures and Zeal Capital Partners, with participation from FIS, Mendon Venture Partners and The 98. Kornhauser declined to disclose a valuation.
The startup was also previously identified as an up-and-coming fintech by insiders for a list Insider originally compiled last fall.
Stratyfy works to help lenders eliminate bias
Stratyfy uses machine learning algorithms to help lenders remove sharp cutoffs — such as those based on credit history lengths or current income — that are often used in their credit decisions.
Much has been written about how biased data can skew automated underwriting. Stratyfy’s product strives to give lenders the tools to detect bias and then help them find what’s driving that bias. Doing so will allow lenders to make changes so the bias doesn’t propagate forward in their ongoing decisions, Kornhauser said.
The core engine uses a lender’s traditional credit data, in addition to alternative data, to provide an overview of factors in a given borrower’s profile. So if Kornhauser was denied credit because of her low current income, the model could spotlight other factors, such as rental or usage data, to compensate for other areas of risk.
Stratyfy works with large banks, fintech lenders and insurance companies across consumers and small businesses. The startup has also built a partnership with a major bank vendor, which can help Stratyfy reach community banks and community development financial institutions, Kornhauser said.
The capital will be used to grow Stratyfy’s team from 18 to 25 by the end of the year, with hires concentrated in engineering and data science, as well as marketing, Kornhauser said.
A case study with a US-based lender using historical data found that the lender accepted only 30% of “good borrowers”, or those who later paid back their loans. With Stratyfy’s core engine, lenders were able to approve 72% of good borrowers while experiencing a slight reduction in expected default risk, Kornhauser said.
