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Should All FI’s Follow Wells Fargo’s Lead and Create A Tech Team For AI and APIs?

Reuters indicates that Wells Fargo has created a new organization to focus on machine learning and to establish new business opportunities utilizing APIs (in 2016 Mercator indicated these were 2 of the 3 technologies banks must implement in 2017. That publication can be downloaded for free here):“The bank also announced that it had appointed Danny Peltz, head of treasury, merchant and payment solutions, to head business development and strategy for its combined payments businesses.

Peltz's group, which comprises of the bank's consumer, small business, commercial and corporate banking payments businesses, will also be tasked with establishing relationship with other companies in the payments landscape. It will also be in charge of the bank's new API (application program interface) services, or technology that allows customers to integrate Wells Fargo products and services into their own applications.”

The bank also established a team dedicated to advancing machine learning to be led by Steve Ellis, head of Wells Fargo's innovation group:“Wells Fargo's AI team will work on creating technology that can help the bank provide more personalized customer service through its bankers and online, the bank said on Friday. It will be led by Steve Ellis, head of Wells Fargo's innovation group.

Well Fargo’s AI focus comes as banks and other large financial institutions increase their investment in the emerging technology which seeks to train computers to perform tasks that would normally require human intelligence.

Projects range from systems that can spot payments fraud or misconduct by employees, to technology that can make more personal recommendations on financial products to clients.”

Despite this reorganization the real opportunity in machine learning is not to improve the technology. The opportunity is in teaching operational business unit managers how to identify where existing machine learning tools can be applied to reduce costs and improve operational accuracy and efficiency to better serve customers. VC dollars and universities are advancing machine learning tools at an incredible pace and making those tools available, often as open source software. The current problem is that few business managers realize how little the solutions cost or where the technology can be applied. That’s the real low hanging fruit!|Overview by Tim Sloane, VP, Payments Innovation at Mercator Advisory Group

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