Rogo Raises $50 Million to Develop AI-Powered Investment Banker

Tech startup Rogo raised $50 million to build an artificial intelligence-powered Wall Street analyst.

The company’s Series B round brings Rogo’s total funding to $75 million, according to a Wednesday (April 30) press release. The company will use the funding to boost investment in financial reasoning models and autonomous AI agents.

“Finance is about more than efficiency — it’s about seeing what others cannot,” the release said. “Wall Street’s best analysts pair hard data with creativity and ruthless clarity of thought. That’s the bar we’ve set for Rogo.”

While the company is still working on its “ultimate vision of a true AI analyst,” clients are seeing results, per the release. Among them is Patrice Maffre, international head of investment banking at Nomura, who said in the release that Rogo “enables our teams to analyze market data and identify opportunities with unprecedented speed and precision, while allowing our bankers to focus more deeply on client relationships and strategic advisory.”

The banking sector is divided on the potential impact of tools like Rogo’s, the Financial Times reported Wednesday. Some think the added efficiency will lead Wall Street banks to reduce their entry-level positions. Others say these products will give banks more freedom to work on more deals, which will mean hiring more people.

“Banks that adopt AI will win more deals, will generate more revenue and will be higher revenue per employee and they’ll want more bankers,” Rogo founder Gabriel Stengel said, per the report. “The only way to get deal-revenue-generating bankers is to train them and create MDs. And you can only do that if you have junior bankers who rise to that level.”

PYMNTS explored the use of AI in helping banks combat fraud Wednesday in a conversation with Eric Stratman, senior director of analytics and insights at ValidiFI.

“A lot of the buildout is at the front end of the transaction, and once you implement that solution, it provides those answers seamlessly in the transaction,” he said.

“The machine learning and AI algorithms can analyze hundreds of thousands of transactional patterns that can then be used to mitigate fraudulent activities” so that clients can OK more transactions with a better sense of the security of the transaction, he added.

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