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Machine learning is now used in Wall Street dealmaking, and bankers should probably be worried

It has been said that Wall Street dealmaking is more art than science. That could be changing.

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JPMorgan, which is spending big on technology as it looks to cut costs and increase efficiency, last year launched a predictive recommendation engine to identify those clients which should issue or sell equity. And now, given the initial success of the engine, it's being rolled out to other areas.

Matt Zames, chief operating officer at JPMorgan, ran through the bank's tech strategy in a letter titled JPMorgan's 328-page letter to shareholders.

Included in the letter alongside talk of robotics, new design standards and a private cloud platform was reference to the Emerging Opportunities Engine. The letter said:

"We also use machine learning to drive predictive recommendations for Investment Banking. Last year, we introduced the Emerging Opportunities Engine, which helps identify clients best positioned for follow-on equity offerings through automated analysis of current financial positions, market conditions and historical data. Given the initial success of the Emerging Opportunities Engine in Equity Capital Markets, we are expanding it to other areas, like Debt Capital Markets, similarly basing predictions on client financial data, issuance history and market activity."

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JPMorgan isn't the only Wall Street bank applying technology to dealmaking.

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