Banking on AI: How financial institutions are deploying new tech. American Banker Newspaper. By Frank Gargano March 19, 2024 11:23 AM
Despite
both consumer and institutional interest in artificial intelligence continuing
to grow across the financial services industry, the majority of leaders are
still unsure about the technology and its potential uses — leaving a select
group of executives to lead their organizations into the fray.
Arizent, the publisher
of American Banker, surveyed 127 financial institution professionals to find
out how traditional and generative AI is unfolding in the industry with respect
to applications, risks versus rewards, impact on the workforce and more.
Respondents represent banks ranging from less than $10 billion of assets to more than $100 billion of assets, as well as credit unions of all asset sizes.
The results showed that familiarity is the largest hurdle for adoption. Tech-minded changemakers helping prepare their organizations for AI said the top two things they are doing are researching providers and attending industry conferences or events on AI. They are also creating working groups for responsible AI usage and educating stakeholders.
Among banks and credit unions that have begun using AI, many have adopted tools for navigating contract negotiations, improving loan underwriting procedures, speeding up internal development projects and more.
But with the White House's executive order on AI and uncertainty about what bank regulators might say about the technology, financial institutions and tech vendors alike are concerned about compliance risk.
James McPhillips, partner at Clifford Chance, said regulators abroad are more progressive than their American counterparts when it comes to overseeing the intersection of banking and technology, including the recent passage of the European Union's Artificial Intelligence Act. This disparity has left financial institutions pondering what similar efforts will look like domestically.
"As it stands, federal regulators appear to be planning to use existing laws to regulate the use and deployment of AI, but banks have not yet seen how those regulators will actually enforce those regulations in the context of AI," McPhillips said.
Below are highlights of the report's findings that give deep insight into how leaders are getting better informed about the implications of AI and whether or not it can pave the way for future innovation.
Testing AI understanding
Bankers'
understanding of AI in its various forms varies, creating numerous
opportunities for further education on the distinctions between traditional and
generative AI.
While roughly 97% of respondents polled on how familiar they were with AI said
they were either very or somewhat familiar with the tech, only 74% had some
understanding of the difference between the two main forms of AI. Twenty-six
percent had no understanding whatsoever.
This knowledge gap has left C-suite executives scrambling to find qualified
talent for the somewhat newly-codified role of
chief AI officer and to fill other AI-related roles.
Research departments within large banks such as JPMorgan Chase, Wells Fargo and
U.S. Bank are often charged with spearheading research on emerging technology
like generative AI, as well as educating others across the organization on
potential use cases.
Those surveyed held that automation and marketing were
top-of-mind fields that stand to benefit most from AI.
"We are receiving a lot of interest by our customers over AI, but at the
same time, they are cautious about [generative AI] and the risk for
hallucinations, which is expected in the financial industry," one
respondent said. "I do think that using AI to perform basic tasks is the
safest route until [generative AI] can be more reliable."
The tool that is often credited for the recent boom in consumer interest
is OpenAI's large language model
ChatGPT, which 73% of those surveyed said they have used for
either personal or professional reasons. But that figure drops off
significantly for similar offerings like Bing AI and Google's Gemini (formerly
known as Bard), recording 35% and 20% usage respectively.
Niche tools including the developer platform GitHub's copilot, Wolfram Alpha
and the San Francisco-based AI startup Anthropic's Claude were more obscure at
15%, 11% and 7% of recorded users.
"Probably the most common way that [AI] is used now is ChatGPT to bridge
the gap in areas that those in my profession are unsure of, such as coding or
coming up with a starting point for ideas," another respondent said.
Overall AI attitudes
Asked
how they feel about the pace of innovation in AI, more than 60% of respondents
felt that both traditional and advanced AI technologies are evolving too
quickly, while 37% say change is coming at the right speed. This has made vetting external partners to
ensure proper frameworks for governance of increased
importance.
"It is important to note that the use of AI in banking is still in its
early stages, and banks should carefully evaluate AI vendors based on their
specific needs and requirements," John King, a partner in the business
transformation practice at Lotis Blue Consulting, said in an American Banker opinion piece.
That hasn't stopped those who consider themselves "fast adopters"
from forging ahead, as 56% are already using AI or expect to use it soon for
work or personal reasons.
Respondents were more willing to trust AI in their personal lives with uses
ranging from predicting car or household maintenance needs (57%) to providing
financial recommendations for investing or budgeting (56%). Tasks that fell
lower on the list include matchmaking with romantic partners (12%) and finding
caregivers for loved ones (9%).
When it comes to work, surveyed bankers mainly trust AI to assist humans — in
the form of copilots.
Helping both employees and customers with standard queries were the top two use
cases that banking professionals were confident that AI could be
mostly-to-wholly responsible for, respectively, garnering 72% and 69% of
responses. Fraud detection, report generation and cybersecurity also
ranked high on the list.
Banks and credit unions alike
have employed AI-powered chatbots for consumers to help relieve the pressure on
customer service representatives and free up time for more complicated
requests. Use cases for employees specifically, however, haven't seen the same
level of adoption.
While 18% of respondents that have access to chatbots use them for
transcription services, an equal percentage of bankers that also have access
choose not to use the tools. Similar disparities were seen throughout this
prompt in areas like navigating benefits, managing reimbursements and employee
onboarding.
Generating interest in generative AI
Respondents
were polled on how (if at all) they employ generative AI in their day-to-day
lives, as well as the general sentiment and pace of adoption within their
organization.
Generative AI is classified in the report as technology that "leverages
large language models and describes algorithms (such as ChatGPT) that can be
used to create new content, including audio, code, images, text, simulations
and videos."
Roughly 61% of bankers said they use generative AI in their personal and/or
work life. While that statistic is promising on an individual basis, results
for adoption at an institutional scale are more staggered.
More than half of global and national banks surveyed are implementing gen AI at
some level over the next 12 to 18 months, recording significant progress in the
more than $100 billion asset class. Roughly 40% of regional banks with less
than $100 billion are also adopting gen AI.
Citi is one such example. The bank currently plans to have a
roadmap to deploy the GitHub Copilot for all 40,000 of its
developers by mid-April, as well as other applications for updating legacy
software and composing initial drafts of compliance assessments.
"I do believe it's a technology that will, in a sustainable way, have a
long-term impact on how we do work for a couple of decades to come,"
Shadman Zafar, chief information officer of personal banking and wealth
management at Citi, said in an earlier
interview with American Banker.
Credit unions are also eager to add gen AI tools to their tech stacks, but on a
smaller scale when compared to banks. Approximately 13% are focusing on
small-scale implementations for specific purposes, and 27% are incrementally
wading into the space with individual pilot projects.
Community banks,
those with less than $10 billion of assets, recorded the lowest percentages of
gen AI adoption at 28%. The majority of respondents said they are still in the
exploratory stage and researching different products, totaling 61%.
Much like traditional AI tools, general use cases for gen AI revolved around
improving office productivity and helping fight fraud with 45% and 36%,
respectively. Customer-facing applications focus more on marketing
communications and helping customer service employees answer questions.
(Not so) smooth sailing ahead
Bankers
also weighed in on the potential risks associated with large language models.
Tied for the top spot, 80% of those surveyed said they were very to somewhat
concerned that either inaccurate information or the likelihood of bias built
into the models and decisioning process posed a significant risk to their
business. Close behind was explainability of the models at 78% and degradation
of client trust and transparency with 77%.
Fears of bias have been an omnipresent worry for many executives pushing
for change in the traditional
methods of assessing a consumer's creditworthiness. More
recently, the $171 billion-asset Navy Federal Credit Union has come under fire
for allegedly discriminating against
minority applicants for home loans.
"As we reflect on the losses incurred by banks due to exclusive
practices, it becomes clear that inclusivity is not just a moral imperative but
a business necessity," William Michael Cunningham, founder of Creative
Investment Research, said in an American Banker opinion piece.
A majority of bankers, roughly 75%, agree that to ensure that AI tools are used
responsibly, international standards and stronger guardrails are vital. Bank
regulators say that current regulations and tools
are enough to shield the public and the industry from the
risks associated with AI.
Without this framework in place, the pace of adoption across the banking
industry will continue to be
slow.