As artificial intelligence (AI) continues to reshape the financial sector, U.S. banks are deploying AI-driven strategies to bolster deposit retention and attract new customers. This trend reflects heightened competition in digital banking and the increasing mobility of interest-sensitive funds.
According to a recent report by Joo Young Min, a Korea Financial Research Institute researcher, American banks leverage AI to reduce customer churn and offer tailored deposit services. The report, published on May 10, outlines how real-time analytics and automation give banks a competitive edge.
Following aggressive interest rate hikes by the Federal Reserve after the COVID-19 pandemic, U.S. banks have experienced a marked slowdown in deposit growth. According to the report, deposit balances fell by 5.0% in May 2023, and as of March 2025, the year-over-year growth was just 2.7%—a steep decline compared to the 22.9% surge during the pandemic.
Despite this, Joo notes that AI is delivering tangible outcomes. “Through real-time data analysis and automated services, banks are fundamentally reshaping their deposit strategies,” he said.
One notable example is RBC’s “NOMI Find & Save” service, launched by Royal Bank of Canada, a leading North American financial group. The AI-powered feature analyzes user spending patterns and automatically transfers surplus funds into savings accounts. In 2023, RBC reported that users saved an average of 495 USD per month (approximately 690,000 KRW).
Another AI innovation gaining traction is real-time interest rate customization. These systems effectively retain rate-sensitive customers who might otherwise switch to competitors.
Goldman Sachs has incorporated AI into its digital platform Marcus, enabling real-time, personalized interest rate offers. Similarly, DBS Bank, Singapore’s largest financial institution, uses an AI-based dynamic rate system to minimize customer attrition and boost acquisition.
Joo adds that AI and machine learning technologies allow banks to monitor cash flows and deposit migration in real time, enabling early detection of large-scale capital shifts (hot money movements) and reducing the risk of unexpected liquidity loss.
While Korean banks have started adopting AI, consumer-facing applications remain limited, often restricted to chatbot-based customer support. Joo stresses the need for greater investment in scalable AI infrastructure, emphasizing that practical implementation is critical for long-term competitiveness and sustainable growth.