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When a small or medium-sized business (SMB) approaches its bank with a request for credit, there is only a 20% chance that the business will qualify for full funding. 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 companies also face challenges in providing credit to their customers. These companies now need to build their own models, processes, and technologies. Lama AIfounded this year, hopes to change that through its AI-powered platform, which it says allows its partners to reach customers quickly while offering a wide range of services. financial products while also targeting the level of risk.
Lama AI says fintech partners can avoid building their own secure lending infrastructure, models and credit facilities while still enjoying increased approval rates. In addition to being a lengthy and expensive process, Lama AI says that building an in-house credit product also limits the types of loans that can be offered and the user base that can be served.
Omri Yacubovich, Co-Founder and CEO at Lama AI.
“Not only are the loan processes required by traditional financial institutions lengthy and rigorous,” says Yacubovich, “… the entire industry has difficulty assessing the risk to small businesses,” says Yacubovich. . We equip our banking partners with unsurpassed digital flows and streamlined processes that ensure accurate underwriting data and details, plus an extension that can meaning for their existing product offerings and credit boxes. “
How Lama AI works
Lama AI, which recently announced a $9 million seed investment, leverages first and third parties and the open web data opportunity to provide better data and referrals. The company says the platform reduces paperwork and filing times without affecting the data required for complete and accurate underwriting. Using the resulting dataset, Lama AI will then automatically match a loan opportunity with the most relevant lending opportunity in the network, based on each partner’s preferences.
For example, a banking partner might see a customer need for bill factoring, which could be a loan product that the bank does not currently offer.
“Up until now, customers would look to another institution for that product, eroding the customer’s relationship with their primary bank,” Yacubovich told VentureBeat. “With Lama AI, the bank can easily launch any loan product with no balance sheet risk in a matter of days and can even continue to make loans in-house.”
Banks can also customize the offer, for example limiting the offer to a 10% APR or excluding lenders within a 100-mile radius of their own branches.
In another example, Yacubovich said, a bank had a risk policy that limits its ability to lend to companies that have been in business for less than two years (a common restriction). An individual who owns multiple profitable businesses looking for capital to expand their new one-year-old trucking operation. Instead of denying this loan request (and putting the entire business relationship at risk), with Lama AI, banks can provide loans at bank rates to their customers by outsourcing credit risk for a partner bank with matching needs.
“Data already available from Lama’s beta banking partners shows that the bank’s transaction flow adoption rate increased by an average of 300%, while reducing the adoption process from a few months to a few,” said Yacubovich. day”.
Some of the additional features in Lama AI’s roadmap include automatic portfolio analysis and appetite adjustment based on the lender’s current portfolio, as well as correlation with macro changes. global scale.
Today’s funding round is co-led by Viola Ventures and Hetz Ventures and includes Foundation Capital and SixThirty.
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