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AI in Banking – An Analysis of America’s 7 Top Banks

While tech giants tend to hog the limelight on the cutting-edge of technology, AI in banking and other facets of the financial sector is showing signs of interest and adoption even among the banking incumbents.

In this article we set out to study the AI applications and innovations at the top banks, helping you to answer the following questions: Through quotes from company executives and data from our AI in Banking Vendor Scorecard and Capability report (interested readers can download the Executive Summary Brief), this article serves to present a concise look at the implementation of AI at seven of America’s top commercial banks by revenue.

First, we’ll provide some insights about the state of AI in banking we discovered through exploring our data and interviews with banking executives Readers with a broader interest in AI’s applications across the financial sector may be interested in reading our article Artificial Intelligence in Finance, which covers a wider array of applications beyond the top US banks.

The full breakdown of AI vendor product offerings by function is provided in the graph below: We should note that banks are likely understating their use of AI for other use-cases, and the banking experts we interviewed for our report and our AI in Banking podcast all agree that banks are investing in AI for compliance and risk monitoring more than any other business area.

At the same time, banks are likely overstating their use of AI for customer service applications, including chatbots because: It will be a while before the technology has advanced enough for chatbots to generate natural language and hold conversations with customers more often than they’re routing customers to customer support agents.

Lastly, our research found a number of top banks referring to AI as an “augmenting” force for their employees, not a “replacement.” To us, this seems to be a necessary move of the communications department, but a disingenuous way to describe AI’s potential impact on jobs, which will most likely involve both “augmenting” and replacing human beings outright.

Unlike many modern tech giants, old banks often have thousands of employees performing mundane paperwork and “legacy” processes, many of which may require complete elimination once machines can replace humans at the desk.

The Emerging Opportunities Engine, introduced in 2015 and discussed in a letter to shareholders, purportedly uses machine learning and natural language processing to help “identify clients best positioned for follow-on equity offerings.” The technology has proven successful in Equity Capital Markets and the company stated their intentions to expand it to other areas, including Debt Capital Markets, but it’s unclear if this has happened yet.

Wells Fargo hasn’t publicized many artificial intelligence initiatives, but Steve Ellis, head of the bank’s Innovation Group, seemed eager to leverage AI in a 2017 press release for a chatbot pilot: AI technology allows us to take an experience that would have required our customers to navigate through several pages on our website, and turn it into a simple conversation in a chat environment.

Katherine McGee, Head of Digital Product Management at Wells Fargo, elaborated on one of these prompts in an email to Bank Innovation: If a customer receives an incoming deposit which is not in their usual pattern of transactions and is not needed to meet their normal expenses or scheduled payments, we can highlight the deposit and suggest the customer save the funds.

Consistent with our high-tech, high-touch strategy, we’ll continue evolving our best-in-class digital banking capabilities, including Erica, to provide clients relevant, timely guidance and help make managing their finances easier.

Although the demo video below shows how Feedzai’s software works for eCommerce companies (and is admittedly a little corny), the principles it describes can certainly apply to banks: Feedzai’s software will purportedly monitor customer payment behavior for deviations from that customer’s normal payment activity.

The software is explained further in the video below and a promotional video can be found on US Bank’s website: According to US Bank, using Expense Wizard, a hiring manager can provide a virtual card to a candidate via the app, setting a card limit via US Bank.

PNC invested $1.2.billion over five years, according to its 2016 annual report, into modernizing its “core infrastructure and build[ing] out key technological and operational capabilities,” with the objective of faster, more secure and more stable operations and services.

Still in the early stages of its tech strategy, the company’s initial focus has been on the consolidation of its data centers and a major shift to an “internal cloud environment.” We can presume that the company’s infrastructure upgrades will help them leverage data and implement artificial intelligence and machine learning.

Examples include “data requests from external auditors” and “funds transfer bots” which help “correct formatting and data mistakes in requests for dollar funds transfers.” The video below provides an explanation for how Blue Prism’s AI software works: Former Senior Executive Vice President and Global Head of Client Service Delivery at BNY Mellon Corp, Doug Shulman, said this about the bank’s investment in RPA: If you think about smart automation, robotics is a piece, workflow is a piece, and we’re combining smart forms, optical character recognition, workflow and robotics to get momentum around automating tasks.

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