The study aimed to explore the role of artificial intelligence (AI)-driven solutions in reducing digital banking fraud and their impact on restoring customer trust. This study narrowed the gap in the literature by exploring the connection between AI fraud-detection systems and customer confidence in digital banking services. This study employed a mixed-methods approach, combining quantitative surveys of banking customers concerning their experiences with digital fraud and perceptions of AI’s efficacy, and interviewed banking professionals and AI specialists. Statistical analysis examined relationships between AI utilization, AI integration in fraud prevention and customer trust recovery. The study reveals prevalent digital banking fraud types include phishing, vishing, identity theft, malicious software, and account takeover. Age and AI tools for fraud detection correlate, but education doesn't. AI-driven systems boost customer trust. This study explores the connection between AI-driven fraud detection solutions and customer trust restoration in digital banking, focusing on its impact on user experience after fraudulent events. AI-driven fraud detection systems enhance customer trust, potentially leading to adoption of digital banking solutions. Financial regulators and policymakers need to support AI integration for improved security measures and trust enhancement.