Pagaya, a fintech specializing in AI-powered asset management, is expanding into real estate, auto loans, corporate credit, and mortgages after a $25 million Series C financing round led by Oak HC/FT, a health care and fintech venture firm.

The latest influx of capital comes after the firm, in February, announced it had raised $100 million for a consumer credit asset-backed security (ABS) fully managed by AI. Since its launch three years ago, Pagaya has grown to manage $450 million for banks, insurance companies, pensions funds, asset managers and sovereign wealth funds. Pagaya has focused on fixed income and alternative credit, offering a variety of discretionary funds.

Gal Krubiner, Pagaya’s CEO and co-founder, told Bank Innovation that institutional investors are thirsty for new sources of attractive risk-adjusted returns and to capitalize on the capabilities and efficiency of AI, machine learning and big data. He said everything is being run by AI and algorithms.

Pagaya’s approach is “totally different,” Krubiner said. “We’re not a big believer in AI enabling people or in any sort of combination of the human being with machines because it’s understood that they are 10 times stronger than us when they are being used right. That’s exactly what we’re proving.”

He said to consider how many parameters and data points go into the typical loan application. “No matter how much time I give you as a credit officer, your ability to price that risk, with 1,500 parameters and data points, is almost meaningless because the machine can do it very well,” he said.

Krubiner said Pagaya’s asset management team of about 30 data scientists and AI specialists uses proprietary machine learning techniques to conduct comprehensive, bottom-up analysis and risk management of assets. The company analyzes hundreds of millions of data points and captures economic and market data to perform asset underwriting and risk assessment.

Also see: Fintech Unfiltered: Pagaya’s CEO Looks at the State of Asset Management in 2019

One of Pagaya’s biggest challenges and opportunities over the next year or so, he said, will be the firm’s expansion into new asset classes.

To use real estate as an example, Krubiner said Blackstone and other big players have allowed institutional investors to invest in real estate by pooling resources and using leverage to buy big and buy cheap.

“But, the truth is, the world has changed,” he said. “The truth is, with the Zillows and other websites, something like 30-40% of all the trades that are being done around housing in the U.S. are now being recorded.”

He said pulling all the information available on all those sites — such as sales prices, rental prices, average incomes, and credit histories — and putting them through algorithms can help predict the future prices of homes.

“We’re seeing more and more things are being recorded online,” Krubiner said. “The ability to extract the data and run them on our AI models will allow us to very quickly determine which types of houses will perform best over time.”

Founded in 2016, Pagaya has about 40 employees with offices in New York and Tel Aviv.