Speaking at the Wave by Vento event in Turin, Italy, Storonsky said Revolut uses techniques similar to those used for large language models to build its own proprietary models trained on customer transaction data, according to the report.
“With 30 to 40 million transactions taking place every day on Revolut, we have a unique dataset to build on,” Storonsky said, per the report.
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Revolut was valued at $115 billion in a secondary share sale this year. The company is Europe’s most valuable startup and is privately valued at more than Barclays or Societe Generale, according to the report.
PYMNTS reported in April that Revolut trained a proprietary AI model called PRAGMA on 40 billion transactions, app interactions and financial events drawn from 25 million users across 111 countries. The model makes decisions about things like who’s likely to commit fraud, who’s a credit risk and which customers are about to leave.
Storonsky told Bloomberg TV Thursday (Oct. 8) that if Revolut pursues an initial public offering, he wants the primary listing to be in the United States. He said this is because of the deep liquidity of the U.S. market.
During the same interview, Storonsky said that once Revolut gets a full banking charter in the U.S., the company aims to roll out credit cards and loans and “dominate” the U.S. market.
Revolut announced Sept. 3 that it got one step closer to launching its American banking business when it received conditional approval from the Office of the Comptroller of the Currency for its U.S. national bank charter. The company said it was working on its remaining applications and approvals with the Federal Deposit Insurance Corporation and the Federal Reserve.
Revolut announced Sept. 16 that it increased the number of full banking licenses it has worldwide to six when it secured a bank license in Colombia. The company had already attained bank licenses in the United Kingdom, France, Australia, Lithuania and Mexico.
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