AI is a hot topic in financial services. And its easy to see why. Increasing margins on transactions, decimated by compliance costs and low interest rates, reaching new market segments, and automating routine tasks, makes AI innovation attractive. And in one sense, FinServ has always been about algorithmic innovation. There is no higher potential ROI than beating the market. Advanced analytics for program trading have been banging away at this goal for decades, with a rich base of advances.

But AI in FinServ is struggling. We looked at the seven most important use cases, from AI-enhanced customer engagement, digital money management, decision management, to robo-administration. We found a low rate of adoption overall and found that different use cases are advancing at different rates because of maturity of AI technology, effect on the customer, and investment appetite.

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