Document Type
Poster Presentation
Publication Date
Spring 2026
Abstract
Renewal risk, the uncertainty surrounding whether customers will continue existing financial relationships such as loans, deposits, credit lines, or insurance products, poses a growing challenge for modern banks because customer retention is critical for revenue stability, cross-selling opportunities, and long-term profitability. This study examines how the adoption of artificial intelligence (AI) in banking interacts with macroeconomic conditions to influence renewal risk and customer attrition. Specifically, the research addresses three primary questions: (1) whether macroeconomic conditions, such as perceived economic health, inflation concerns, unemployment expectations, and personal financial confidence, affect the likelihood and timing of banking product renewal; (2) how AI adoption, measured by adoption stage, breadth of AI features used, and frequency of use, influences renewal behavior; and (3) whether macroeconomic conditions moderate the relationship between AI adoption and renewal outcomes. Using cross-sectional survey data collected from banking customers, the study analyzes the effects of AI adoption and perceived macroeconomic stress on renewal behavior, time-to-renewal, and renewal intentions while controlling for established drivers of customer loyalty including service quality, trust, bank ethics, switching costs, and relationship quality. The analysis tests the hypothesis that favorable economic conditions strengthen the positive impact of AI-enabled banking features on customer renewal, whereas adverse macroeconomic conditions weaken this relationship as customers prioritize cost savings and liquidity preservation. By integrating technological adoption with macroeconomic context, the study provides insight into the conditional effectiveness of AI-driven customer retention strategies in contemporary banking.
Recommended Citation
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