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When a small- or midsized business (SMB)  approaches its bank with a request for credit, there is only a 20% chance that it’s qualified for full financing. Many of these businesses then turn to private lenders and merchant cash advance (MCA) providers, borrowing at potentially double-digit annual percentage rates (APRs). 

On the lender side, fintech players are also challenged in providing credit for their customers. These firms currently need to build their own models, processes and technology. Lama AI, which was founded this year, hopes to change that through its AI-powered platform, which it says enables its partners to onboard customers quickly while offering a range of financial products while targeting risk levels.

Lama AI says fintech partners can avoid building their own lending infrastructure, models and secure credit facilities while enjoying increased approval rates. Beyond being a long and costly process, Lama AI says that building a credit product in-house also limits the types of loans that can be offered and the user base that can be served.

“Eight out of 10 small businesses that seek capital for growth, working capital, hiring, seasonality or any other reason get rejected by their primary bank, in many cases, despite being a loyal customer for many years,” said Omri Yacubovich, cofounder and CEO at Lama AI.


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 “Not only are the borrowing processes required by traditional financial institutions lengthy and demanding,” Yacubovich said, “…the industry, as a whole, struggles in assessing risk for small businesses. We equip our bank partners with superior digital flows and streamlined processes, ensuring accurate underwriting data and insights, alongside a meaningful extension to their current credit box and product offerings.”

How Lama AI works

Lama AI, which recently announced a $9 million seed investment, leverages first- and third-party and open-web data opportunities to provide better data and onboarding.  The platform reduces paperwork and application time without compromising the required data for full and accurate underwriting, the company says. Using the resulting dataset, Lama AI then automatically connects the lending opportunity to the best match in the network, based on each partner’s preferences.

For example, a bank partner may see customer demand for invoice factoring, which is perhaps a lending product the bank does not currently offer. 

“Until now, customers would go to a different institution for that product, eroding the customer relationship with their primary bank,” Yacubovich told VentureBeat. “With Lama AI, the bank can easily launch any lending product with no balance sheet risk in a matter of days, and can even keep loan servicing in-house.”

The bank can also customize the offering, for example, limiting offers to 10% APR, or excluding lenders within a 100-mile radius of their own branches. 

In another instance, Yacubovich said, say a bank has a risk policy that limits its ability to lend to firms that have been in business for under two years (a common restriction). An individual who owns multiple profitable businesses is looking for capital to expand their new one-year-old trucking operation. Rather than reject this loan request (and risk the entire business relationship), with Lama AI, the bank can offer a bank-rate loan to their customer by outsourcing the credit risk to a partner bank with a suitable appetite.

“Data that is already available from Lama’s beta bank partners shows a 300% average increase in bank deal-flow acceptance rate, while reducing the intake process from months to days,” said Yacubovich. 

Real-world performance 

Some additional features on Lama AI’s roadmap include portfolio analysis and automated appetite adjustment based on the lender’s current portfolio, as well as correlation to global macro changes.

Today’s funding round was co-led by Viola Ventures and Hetz Ventures and includes Foundation Capital and SixThirty.

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