How AI Can Calm Customers Unnerved by Economic Upheaval
By Charles Gorrivan and Victor Swezey
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Executive Summary
- As the economy swings on tariff threats and geopolitical uncertainty, banks are leaning on generative AI to keep anxious customers on track.
- AI tools are also helping banks mine behavioral data to stay ahead of customer needs in everything from loan defaults to life events like moving or switching jobs.
- Meanwhile, AI is rapidly becoming central to banks’ own risk management, parsing real-time data to flag anomalies and emerging risks faster than legacy systems.
Markets have been on a wild ride since US President Donald Trump’s announcement of sweeping reciprocal tariffs on all of America’s trading partners. In the days following the April move, U.S. markets recorded historic single-day trading volumes and some of the sharpest intraday swings in half a century.
Many customers are asking more questions about their personal financial life because of the recent volatility, bankers say. At the same time, forecasting is becoming harder as instability disrupts the financial models banks rely on to help customers plan big decisions — from taking out a loan to buying a car.
To stay ahead of the curve, banks are turning to generative AI to navigate the economic swings and retain nervous customers. AI tools are helping banks to build more adaptive models that predict everything from loan defaults to life events like moving or switching jobs. They are also transforming frontline service. Virtual assistants are being used to triage basic queries and help humans flag customer needs.
In recent years, banks at all levels have been investing heavily in generative AI. JPMorgan, the largest U.S. lender, has been at the forefront of this shift. Its AI tools are now deployed on nearly two-thirds of the company’s 320,000 employee desktops, according to Karen Donnelly, co-head of global private bank product and head of digital for JPMorgan’s U.S. Private Bank.
Amid the recent volatility, JPMorgan’s AI investments have begun to pay dividends. The firm told The Financial Brand it deployed its generative AI tools — Connect Coach and LLM Suite — to help advisors manage a surge in client concerns following President Trump’s tariff announcements in April. Within its asset and wealth management arm, the tools enabled advisors to rapidly compile detailed memos, summarise client account data, and surface timely market insights.
According to Donnelly, the tools reduced data retrieval and documentation time by up to 95% compared to traditional methods, significantly cutting down on what she called routine “no-joy” tasks.
“This has enabled our teams to respond promptly to market swings, ensuring that advisors are well-prepared to address heightened client inquiries and deliver timely, personalized investment advice,” says Donnelly, adding that J.P. Morgan is actively exploring additional AI applications to strengthen fraud prevention, optimise trading strategies, and enhance operational efficiency.
Want more insights like these? Check out Jack Henry’s content hub: Maximize the Impact of AI to Ignite Innovation
How Fifth Third is Using AI to Address Customer Anxiety
This is not the first time banks have turned to AI to support customers in times of stress. During the early days of the COVID-19 pandemic, Fifth Third Bank fast-tracked the rollout of its AI chatbot, Jeanie, to meet rising customer anxiety, according to Michelle Grimm, the bank’s senior director for conversational AI.
“The pandemic created an urgent need to support our customers, as well as our call center agents,” Grimm told The Financial Brand. She said Jeanie, which uses a non-generative natural language understanding model, enabled agents to handle multiple chat conversations simultaneously — helping absorb the flood of nervous customer queries.
Volatility is expanding AI’s role far beyond financial planning and customer support. Marco Santos, global chief executive at GFT Technologies SE — a consulting firm that advises firms like HSBC, Santander and Deutsche Bank — says AI is becoming central to core risk assessment functions such as underwriting, fraud detection, and credit scoring. In these areas, where traditional models are struggling to keep pace with sudden behavioural shifts, AI can analyse real-time data from mobile apps, digital wallets, and transaction histories to flag anomalies and adapt to emerging risks faster than legacy systems, Santos said.
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Economic Volatility Has Compressed Reaction and Response Times
Market uncertainty has also compressed the traditional monthly cycles banks use to review credit, adjust offers, and make lending decisions, according to Santos. In more stable markets, these processes ran on a predictable rhythm. “With more volatility, these cycles must be reduced,” says Santos. “You need to collect more data, you need to organize them better, and we need to have AI to personalise this.”
As employees assist customers anxious over market swings, generative AI can also help fine-tune communication to ensure the tone of each message fits the moment, according to Philip Suckow, vice president of innovation at Wausau, Wisc,-based IncredibleBank.
IncredibleBank has implemented an AI assistant — which it calls “Banno” — from financial services provider Jack Henry. Employees use the tool to help them answer customer inquiries on the bank’s mobile app. Instead of responding directly, Banno suggests replies that a human representative can approve or edit before sending.
One of Banno’s key benefits is helping employees adjust the formality of their messages , depending on the context of the conversation and the customer’s needs. Amid recent macroeconomic uncertainty, Suckow said employees have been leaning on the tool’s recommendations for a “compassionate tone” in crafting replies.
With abnormal fluctuations causing a spike in customer inquiries about refinancing, Banno has also adapted by learning from repeated conversations. “That suggested response only continues to get smarter based on the amount of conversations that are coming in on that topic,” said Suckow, who noted that AI has helped IncredibleBank cut its response time for inbound digital conversations by up to 83%.
Recent AI use cases have looked different at New York City-based fintech MoneyLion, whose customers skew younger and are often underbanked, building credit or just beginning to invest. For this group, market volatility hasn’t caused a dramatic behavioural shift — largely because financial insecurity is already a constant. “I think it’s continued shell shock for them,” said MoneyLion’s global chief technology officer, Phill Rosen.
With AI ingesting data from both MoneyLion’s neobank and embedded finance unit, Engine — including credits, debits, applications, approvals, content engagement, and third-party product usage — the company can respond to customer signals in real time, even amid unpredictable market conditions. “Based on a consumer expressing concern over X, Y, and Z,” Moneylion is able to recommend products from across its marketplace and platform, said Rosen. “AI allows us to do that in an expanded way beyond, you know, traditional data science models.”
AI is Critical to Operational Agility
The need for that kind of agility is only growing, according to Santos, who says that banks should no longer treat market turbulence as a temporary shock. “Volatility is the rule of the game over the next years,” he said, warning that banks should expect “upside down news” on a near-weekly basis that is capable of reshaping consumer behaviour and disrupting financial predictions.
For Santos, AI will be critical to navigating that dynamic. The GFT global CEO estimated that AI could help financial institutions grow new customer acquisition by at least 30% over the next few years.
“We need to deploy more agents in order to understand, predict and personalize the customer experience right in order to support volatile behavior,” he said.
Even so, Suckow cautioned that AI is not about removing people from the equation. “We want to keep the human engaged, because we believe that people still bank with people and relationship,” Suckow said.
For Suckow, AI is most valuable when it makes humans more efficient — not when it replaces them. That distinction may matter most in times of uncertainty. “How can we make the people on our side of the conversation more accessible, faster to respond?” he said.
JPMorgan’s Donnelly echoed that view. “It is the blend of technology with our seasoned expertise that truly strengthens client confidence,” she said.
