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When a small or medium-sized business (SME) approaches its bank with a loan application, there is only a 20% chance that it will qualify for full financing. Many of these companies then turn to private lenders and cash advance providers (MCAs) and borrow at potentially double-digit annual percentage rates (APRs).
On the lender side, fintech players are also challenged in extending credit to their customers. These companies currently need to build their own models, processes and technology. Llama AIFounded this year, it hopes to change that through its AI-powered platform, which enables its partners to quickly onboard customers while offering a range of financial products while addressing levels of risk.
Lama AI says fintech partners can avoid building their own lending infrastructure, models and secure credit facilities, while benefiting from higher approval rates. Besides being a long and costly process, Lama AI says 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 seeking capital for growth, working capital, staffing, seasonality, or any other reason are in many cases rejected by their primary bank, despite being a loyal customer for many years,” said Omri Yacubovich, co-founder and CEO at Lama AI.
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“Not only are the lending processes required by traditional financial institutions long and demanding,” Yacubovich said, “…the industry as a whole struggles to assess risk for small businesses. We equip our banking partners with superior digital flows and streamlined processes. , ensuring accurate insurance data and insights, as well as meaningfully expanding their current credit box and product offerings.”
How Llama AI works
Lama AI, which recently announced a $9 million seed investment, leverages first- and third-party and open-web data capabilities to deliver better data and onboarding. The platform reduces paperwork and application time without compromising data required for complete and accurate adoption, the company says. Using the resulting dataset, Lama AI then automatically matches 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 may be a loan product that the bank does not currently offer.
“Until now, customers would go to another institution for that product, affecting the customer relationship with their primary bank,” Yacubovich told VentureBeat. “With Lama AI, the bank can easily launch any credit product without balance sheet risk within days, and even keep lending in-house.”
The bank can also adjust the offer, for example by limiting offers to 10% APR or excluding lenders within a 100-mile radius of their own branches.
In another case, Yacubovich said a bank has a risk policy that limits its ability to lend to companies that have been in business for less than two years (a common limitation). A person who owns multiple profitable businesses is looking for capital to expand his new one year old trucking business. Instead of rejecting this loan application (and risking the entire business relationship), Lama AI allows the bank to offer a bank-rate loan to their customer by outsourcing the credit risk to a partner bank with a suitable appetite.
“Data already available from Lama’s beta banking partners shows an average 300% increase in the acceptance rate of bank deals, 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 with 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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