Artificial Intelligence in Finance: A Systematic Review of Applications, Challenges, and Future Research Directions (2010–2025)

Abstract

Background Artificial intelligence (AI) has emerged as a transformative force in the financial sector, reshaping traditional financial operations through advanced analytical capabilities, automation, and intelligent decision-support systems. While AI applications have expanded rapidly across banking, investment management, and financial services, evidence regarding their effectiveness, limitations, and broader implications remains fragmented. This review examines the evolving role of AI in finance by synthesizing empirical evidence on applications, benefits, challenges, and future research directions. Methods A systematic literature review was conducted on empirical studies, industry reports, and peer-reviewed publications examining AI applications in finance between 2010 and 2025. The review analyzed evidence across major AI domains, including machine learning, deep learning, natural language processing, and explainable artificial intelligence (XAI), focusing on their application in predictive analytics, credit risk assessment, fraud detection, algorithmic trading, portfolio management, regulatory compliance, and customer financial services. Results The findings indicate that AI significantly enhances financial decision-making by improving predictive accuracy, automating complex processes, strengthening risk assessment, and enabling personalized financial services. Machine learning and deep learning models demonstrate superior performance compared with conventional approaches, particularly in credit scoring, fraud detection, market prediction, and anomaly identification. However, the review highlights persistent challenges related to data quality, model interpretability, algorithmic bias, cybersecurity risks, regulatory uncertainty, and limited cross-context validation. Explainability and ethical AI governance emerge as critical requirements for the responsible deployment of AI in high-stakes financial applications. Furthermore, AI presents opportunities for advancing financial inclusion, sustainable finance, and real-time financial intelligence. Conclusion AI is fundamentally redefining the future of finance by enabling more efficient, adaptive, and data-driven financial ecosystems. However, realizing its full potential requires balancing technological innovation with transparency, accountability, regulatory alignment, and inclusive implementation. Future research should prioritize explainable, ethical, and context-aware AI frameworks capable of supporting resilient, equitable, and sustainable financial systems.