Impact of Artificial Intelligence on FinTech Innovation and Customer Experience

Abstract

AI has become an essential tool in financial technology due to its ability to make data-driven decisions, ensure continuous access to services, foresee risks, and now personalize service interactions. But the discussion about efficiency has shifted to a harder question: What will be necessary for AI to lead to real innovation in the FinTech business and also to enhance the customer experience without compromising trust, fairness and transparency? This research will answer that question by conducting an original secondary-data empirical study utilizing a structured content analysis of 30 recent articles published in 2021-2026, mostly peer-reviewed journal articles, along with a few authoritative policy reports. Google Scholar-indexed search was conducted to identify the corpus and then coded in terms of the application domain, the innovation mechanism, outcome of the customer experience, methodological designing, trust and transparency factors, and risk and governance issues. Based on these results, five segments have the highest innovation impact for AI—credit scoring and underwriting, fraud detection and digital onboarding, conversational service and self-service systems, robo-advisory, and regulatory technology. In the coded corpus, AI's transformative advantages were most clearly perceived with respect to speed, convenience, personalisation and increased access, subject to transparency, perceived control, institutional trust and blended human oversight. Best outcomes for customer experience were found in low friction, repetitive, and information-rich transactions, and highest risks were identified in ambiguous credit decisions, intrusive data collection and usage, and over-automated service transactions. The study thus concludes that the effect of artificial intelligence in FinTech is not fully captured by the intensity of adoption, but rather by the algorithmic capability, combined with the governance quality, and the customer-centric design. The results provide a research-informed synthesis that can serve the purpose of doctoral research by transforming the concept of an artificial intelligence from merely a tool for automation to a contingent IA for which the value for the customers depends on its explainability, ethical regulations, and context-sensitive design..