Home Merchant cash advance Artificial intelligence (AI) platform aims to provide lenders with improved efficiency and expanded financial product offerings

Artificial intelligence (AI) platform aims to provide lenders with improved efficiency and expanded financial product offerings

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When a small or medium enterprise (SME) approaches their bank with a loan application, there is only a 20% chance that they will qualify 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 (APR).

On the lender side, fintech players are also struggling to provide credit to their customers. These companies currently have to build their own models, processes and technologies. Lama AI, which was founded this year, hopes to change that with its AI-powered platform, which it says enables its partners to quickly onboard customers while offering a range of financial products while targeting risk levels.

Lama AI says fintech partners can avoid creating their own lending infrastructure, models, and secured credit facilities while enjoying increased approval rates. Besides being a time-consuming and expensive 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, hiring, seasonality or any other reason are rejected by their primary bank, in many cases despite being a loyal customer for many years,” said Omri Yacubovich, co-founder and CEO of 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 is struggling to assess the risks for small businesses. our banking partners of superior digital flows and streamlined processes, ensuring accurate underwriting data and information, as well as a significant expansion of their current credit box and product offerings.

How Lama AI Works

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

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

“Until now, customers were going to a different institution for this product, which eroded the customer relationship with their primary bank,” Yacubovich told VentureBeat. “With Lama AI, the bank can easily launch any loan product without balance sheet risk within days, and can even service the loans in-house.”

The bank can also customize the offer, such as limiting offers to 10% APR or excluding lenders within 100 miles of their own branches.

In another case, Yacubovich said, let’s say a bank has a risk policy that limits its ability to lend to businesses that have been in business for less than two years (a common restriction). A person who owns several profitable businesses is looking for capital to expand his new year-long trucking business. Rather than rejecting this loan request (and risking the entire business relationship), with Lama AI, the bank can offer a bank rate loan to its client 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 increase of 300% in banking transaction acceptance rates, while reducing the intake process from months to days,” Yacubovich said.

Actual performance

Some additional features of the Lama AI 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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