The Key to AI is Structured Data, BNY Says

The promise of artificial intelligence around streamlining and enhancing banking processes has enticed most, if not all, financial institutions at this point.

But before jumping to AI, FIs need to get their data straight, according to Jon Theuerkauf, managing director and group head of performance excellence at BNY Mellon.

“Forget AI, I don’t even know what it means,” he said at BluePrism World event today. “Why are we jumping on it, if we haven’t done the basics?”

The “basics,” according to Theuerkauf, is having a structured data ecosystem in place.

“We are now in a transitional phase, and are still three to five years away from integrating operating automated environment,” he said. “For example, it takes a long time to train Watson. Why? Because the data does not land itself easily to allow Watson to learn. So, there needs to be an order around that data, and we are now starting to put things together and taking the chaos out of it.”

Currently, BNY is “consciously incompetent” in terms of adopting AI and automation, and “we are really proud of that,” Theuerkauf added. “We now know what we don’t know, we know that we need ways to structure data, and are still working on how.”

BNY began experimenting with bots and automation last year. In less than 10 months, the bank went from 0 to 200 bots, according to Theuerkauf, and has thus far automated more than 100 processes, with 50 more underway.

“We have $3 trillion in payments a day that run through our shop, would you let a robot handle that process? This was actually the second process we had automated,” he said.

The efforts around structure and RPA — robotic process automation — will, eventually, lead the bank to AI and machine learning integrations. “We are figuring stuff out, putting teams together, and hopefully this will lead us to maturing into a machine learning and AI-enabled world,” Theuerkauf said. “RPA is the ‘doing’ part of automation, AI is the ‘thinking’ part.”

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