Israeli AI fintech co Pagaya raises $25m

Pagaya founders Photo: Inbal Marmari

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The Tel Aviv based company manages investments in consumer credit in the US with a decision mechanism based on artificial intelligence and machine learning.

Israeli fintech company Pagaya has raised $25 million in a Series C financing round only six months after raising $14 million. The company has raised a total of $45 million to date.

Pagaya manages investments in consumer credit in the US with a decision mechanism based on artificial intelligence and machine learning. The company declined to disclose its value for the round, but said that it was higher than in the preceding round.

Leading the financing round was US investment fund Oak HC/FT. All of Pagaya's previous investors also took part, including Viola Ventures, Clal Insurance, GF Investments, former American Express chairperson and CEO Harvey Golub, and bank Siam Commercial Bank, one of the largest banks in Thailand.

The company said that it had conducted another financing round so soon after its preceding round in order to speed up development of technological capabilities and the launching of additional debt products in the US, such as car loans, mortgages, and corporate debt.

Founded in 2016 in Tel Aviv by CEO Gal Krubiner, Yahav Yulzari, and Avital Pardo, Pagaya has 50 employees, 40 of whom are in Israel. The company says that it manages assets for sovereign wealth funds, banks, insurance companies, pension funds, large financial institutions, and private investors.

The company adds that it manages $500 million in debt instruments in the US alone. Its customers include Citibank, Phoenix Insurance, Clal Insurance, Bank Leumi, Bank Hapoalim, and Union Bank.

Pagaya recently agreed on a deal to manage $100 million in investments for a sovereign wealth fund. The company's revenue model is based on 1-2% annual management fees, meaning that its revenue from the new deal will be $5-10 million a year.

Pagaya says that its technology is based on artificial intelligence (AI) and machine learning. It examines candidates for receiving credit and recommends preferred deals to credit companies. According to Pagaya, its algorithm is capable of generating a better return for investors at lower risk. The system uses advanced statistical models to analyze data from databases with millions of loans and identify a correlation between the borrower's credit history and the expected cash flow from the loan. It thereby selects the better borrowers and reduces defaults in the lending company's credit portfolio.

"Credit managers are looking for the five most important variables for deciding whether a person should receive a loan, but we take 1,500 variables into account. The intuition of a credit manager cannot be compared to AI examining this number of variables faster and more precisely," Krubiner explained to "Globes."