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While tech giants tend to hog the limelight on the cutting-edge of technology, AI in banking and other financial sectors is showing signs of interest and adoption – even among the stodgy banking incumbents.
Discussions in the media around the emergence of AI in the banking industry range from the topic of automation and its potential to cut countless jobs to startup acquisitions. In this article we set out to study the AI applications of top banks, helping you to answer the following questions:
- What types of AI applications are currently in use by customers and employees and what applications are in the works at banking leaders JPMorgan Chase or Wells Fargo?
- What common trends do their innovation efforts point to – and what does that mean for the future of banking?
- How much has been invested in AI and emerging tech innovation across leading US banks?
Through facts and quotes from company executives, this article serves to present a concise look at the implementation of AI by the seven leading commercial banks in the U.S. as ranked by the Federal Reserve. Changes in the banking industry directly impact businesses and commerce, and we sought to provide relevant insights for business leaders and professionals interested in the convergence of AI and financial technology.
We’ll explore the applications of each bank one-by-one. The top seven US banks below have been rank-ordered by their size, starting with JPMorgan Chase, the largest.
(Readers with a more broad interest in AI’s applications across the financial sector may be interested in reading our article titles “Machine Learning in Finance“, which covers a wider array of applications beyond the top US banks.)
JPMorgan Chase
JPMorgan Chase has invested in technology and recently introduced a Contract Intelligence (COiN) platform designed to “analyze legal documents and extract important data points and clauses.” Manual review of 12,000 annual commercial credit agreements normally requires approximately 360,000 hours. Results from an initial implementation of this machine learning technology showed that the same amount of agreements could be reviewed in seconds. COiN has widespread potential and the company is exploring additional ways to implement this powerful tool.
The Emerging Opportunities Engine, introduced in 2015 and discussed in a letter to shareholders, uses automated analysis to help “identify clients best positioned for follow-on equity offerings.” The technology has proven successful in Equity Capital Markets and is currently being expanded to other areas including Debt Capital Markets.
First successfully piloted in 2016, the firm plans to officially roll out its virtual assistant technology which integrates a natural language interface “to respond to employee technology service desk requests.” The initial goal will be 120,000 service tickets with future expansion to efficiently address more of the 1.7 million employee requests the company receives each year.
“I have never been more excited about the opportunities ahead. Our focus on innovation and aggressive optimization to meet new challenges will continue to result in dynamic changes to our operating model as we best position our businesses for the future.” – Matt Zames, CEO, 2016 Annual Report
The firm invested over $9.5 billion in technology in 2016, with $3 billion “dedicated toward new initiatives” and a $600 million fraction slated for “emerging fintech solutions.” Specific interests include partnerships with fintech companies and developing new and enhancing current digital and mobile services.
Wells Fargo
In an effort to leverage emerging technologies and help drive the enhancement of its organizational structure, Wells Fargo announced the establishment of a new Artificial Intelligence Enterprise Solutions team in February. Steve Ellis, EVP and head of the company’s Innovation Group, was appointed to lead the new team. The AI group is nestled under the umbrella of the Payments, Virtual Solutions and Innovation group which has three main goals:
“…increase connectivity for the company’s payments efforts, accelerate opportunities with artificial intelligence, and advanced application programming interfaces to corporate banking customers.”
In April, the company began piloting an AI-driven chatbot through the Facebook Messenger platform with “several hundred employees.” This virtual assistant communicates with users to provide account information and helps customers reset their passwords. This is not the first time the company has leveraged the Facebook platform to meet customer needs. In fact, Wells Fargo has communicated with customers through Facebook since 2009. The company reported that it planned to expand its testing phase later in the spring to a few thousand customers.
“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. That’s a huge time-saving convenience for busy customers who are already frequent users of Messenger.” – Steve Ellis, head of Wells Fargo’s Innovation Group
Wells Fargo is also influencing the future of fintech through its competitive Startup Accelerator program which has received over 1,100 applications from over 50 countries since its inception in 2014 and its own Innovation Lab.
Bank of America
Celebrating a decade of mobile banking this year, Bank of America Corporation recently made a bold push into AI technology with the debut of an intelligent virtual assistant named erica. Officially unveiled at the 2016 Money 20/20conference in Las Vegas, described as the world’s largest payment and financial services innovation event, erica is a chatbot leveraging “predictive analytics and cognitive messaging” to provide financial guidance to the company’s over 45 million customers.
Mobile banking has seen steady growth from 12 million customers in 2012 to nearly 22 million in 2016 and is a key representation of the company’s investment in technology. As an integrated component of the mobile banking experience, erica is designed to be accessible to clients 24/7 and perform “day-to-day transactions” in addition to anticipating the unique financial needs of each customer and helping them reach their financial goals by providing smart recommendations.
We want to be there for customers in the moments that matter most. Incorporating artificial intelligence into our mobile banking offering will help customers manage their simple banking needs more efficiently and consistently, which then allows our specialists in our financial centers to spend more time with customers to understand their more complex needs and help them improve their financial lives.” -Thong Nguyen, president of Retail Banking, Bank of America
The company’s reported $3 billion innovation budget in 2016 and the Annual Technology Innovation Summit held in Silicon Valley “to explore potential partnerships, discuss trends and solve some of today’s challenges” positions the company firmly to maintain a bird’s eye view on the latest innovations in fintech. 2016 marked the second-most profitable year in the company’s history and with continued and strategic investment in technology and AI the company is poised for continued record-breaking growth.
CitiBank
With an eye on gaining a competitive edge in the marketplace, Citibank has recently established a succession of innovative partnerships with cutting edge tech companies to expand and improve its services. Through its investment and acquisitions wing, Citi Ventures, the bank boasts a global network of tech companies that participate in its six Citi Global Innovation Labs.
In its portfolio of startup investments, particular attention has been given to ecommerce and cybersecurity. Through Citi Ventures, CitiBank has made a strategic investment in Feedzai, a leading global data science enterprise that works in real-time to identify and eradicate fraud in all avenues of commerce including online and in-person banking. Through its continuous and rapid evaluation of large amounts of data, Feedzai can conduct large-scale analyses.
Fraudulent or questionable activity is identified and the customer is rapidly alerted. The service also assists payment providers and retailers in monitoring and protecting financial activity in connection with their companies. To prevent fraud and monitor potential threats to customers in commerce Feedzai utilizes “machine-based learning” to evaluate “big data” and potentially fraudulent activities.
Citi Ventures’ other investments in the realm of artificial intelligence include Clarity Money which recently announced “$11 million Series B funding round led by RRE Ventures and Citi Ventures.” Citi Ventures has helped to bring this new personal finance application to the market. The Clarity Money app motivates customers to participate in third-party services that can improve financial health. Citi Ventures’ Managing Director Luis Valdich announced the partnership in January of 2017.
“The future of financial services will be transformed by those who can successfully leverage APIs to connect consumers with best-of-breed providers, Citi Ventures is pleased to support Clarity Money, which is committed to responsible finance and is empowering consumers via APIs with actionable insights and third-party products that can help improve their financial health.” – Luis Valdich, Managing Director at Citi Ventures
U.S. Bank
To support its efforts, the bank has already made a sizeable investment (we were unable to find specific figures) in its Minnesota-based Innovation Group which focuses exclusively on artificial intelligence and machine learning practice throughout the twenty-five states where it operates.
The creation and announcement of this role seems from the outside to be a reaction to AI as a trend, rather than a sign of their strong leadership in apply AI in banking and finance. The loud announcement of the role appears to be a PR efforts to – but it comes across as the “me too” announcement of a lagging company.
The description of the new role states that this lead will be expected to “Represent U.S. Bank as a key spokesperson to internal stakeholders, external current and potential customers and partners.”
Further searches related to “U.S. Bank” and “artificial intelligence” don’t draw up much by way of present applications at the bank. However, U.S. Bank’s senior vice president of payments innovation, Arif Ahmed, was interviewed about his perspectives on near-term AI applications, and he seems to share an optimism for conversational interfaces and chatbots.
Another article in American Banker references Chief Innovation Officer Dominic Venturo as expressing optimism for AI’s ability to “augment” human workers, not “replace” them. Venturo also explains a potential application of AI for helping bank associates answer infrequent questions more quickly for it’s customers (the application appears to remain in research and development at the time of this writing).
PNC
Now in the final year of a five-year plan, with an investment of $1.2.billion (as stated in the firm’s 2016 annual report PDF), PNC has been modernizing its the “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 (indeed companies like Cloudera make their living from getting legacy companies up to speed in AI-ready infrastructure), but no direction mention of AI is made in the annual report.
Further research into PNC’s current AI efforts haven’t yielded much else. The firm has published some short PDF resources about chatbot applications, but the PDF itself makes it clear that the article is intended to provoke thought, and is not necessarily indicative of the views or initiatives of PNC. Like most other large companies, AI seems to be in the “awareness” stage at PNC, and time will tell if they will follow or differentiate from their larger US competitors (such as Chase and Wells Fargo, who are both a bit farther ahead of the curve in current AI applications).
Bank of NY Mellon Corp.
The 233-year-old financial institution is banking on “bots,” specifically robotic process automation (RPA), to improve the efficiency of its operations and to reduce costs. RPA integrates artificial intelligence and is carried out not by physical robots but by software applications. These applications known as web robots or Internet bots are programmed to process automated tasks. In May 2017, the bank announcedthat over the past 15 months the company has rolled out more than 220 bots developed by Blue Prism for handling tasks that are often repetitive in nature and normally handled by staff. Examples include “data requests from external auditors” and “funds transfer bots” which help “correct formatting and data mistakes in requests for dollar funds transfers.”
“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.” – Doug Shulman, Senior Executive Vice President and Global Head of Client Service Delivery
BNY Mellon reports that the implementation of RPA has led to the following results:
- 100 percent accuracy in account-closure validations across five systems
- 88 percent improvement in processing time
- 66 percent improvement in trade entry turnaround time
- ¼-second robotic reconciliation of a failed trade vs. 5-10 minutes by a human
From a financial perspective, the corporation estimates that the activity of its “funds transfer bots” alone is responsible for $300,000 in annual savings. These bots cut down on the time employees spend processing payments and resolving data errors. In addition to increased efficiency and reduced costs, in their 2016 annual report, industry competition is emphasized as another reason behind the bank’s increased integration of AI technology.
Concluding Thoughts on AI in Banking
Top US banks all seem to be experimenting with conversational interfaces. Our own “AI Consumer Use” consensus from 2016 also points to a burgeoning enthusiasm for chatbot applications.
The seven leading U.S. commercial banks have prioritized strategic technological advancement with investments in AI applications to better service their customers, improve performance and increase revenue. The future of finance will be heavily influenced by emerging fintech and AI applications setting the stage for increasing competitiveness among the industry’s leading giants.
From our analysis of the top seven US banks, we’ve found an interesting but not surprising trend: It seems that larger banks (at the time of this writing) seem to have more robust AI applications in development and in use. This may reflect the tremendous difficulty of obtaining and retaining machine learning and AI talent. Companies like Amazon, Google and Facebook not only have a more alluring reputation for innovation, but they also have much higher profit-per-employee ratios, allowing them to shower top talent with higher salaries and excellent perks. It’s unlikely that even behemoths like JPMorgan Chase or Wells Fargo will be able to compete well against the tech giants in the AI talent war of the next decade.
In researching these seven firms, “chatbots” and “conversational interfaces” emerges as trends that seem to inspire enthusiasm and excitement in the banking world. It may very well be that more mundane business intelligence or cyber security will eat up most of the AI budget for these large banks, but it’s clear that chatbots have garnered the most excitement from the PR departments and spokespersons of the banking giants we researched.
Our research seems to indicate that the enthusiasm for conversational interfaces is indeed held by startups, not just Fortune 500 banks. Our own AI Executives Consumer Use Consensus shows “chatbots” as the most likely innovation of greatest consumer impact in the next five years.
Lastly, our research found a number of mentioned 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. Interested reader may want to see the quotes from our Artificial Intelligence Risk researcher consensus below, which highlights economic / job loss issues as the greatest near-term AI threat to human wellbeing:
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. Staff-heavy firms (including Accenture, who mostly echoed the same “augmentation” statement in our interview with their CTO) almost unanimously speak of AI in black-and-white terms.
We believe that the future involve a number of disruptive changes that banks (and indeed all modern economies) will have to prepare themselves for.
