Artificial Intelligence in Smart Finance: Applications, Challenges and Future Trends
TL;DR
This study reviews and analyzes major AI applications in smart finance, including heterogeneous data fusion models for credit risk assessment, real-time intelligent algorithms for financial fraud detection, and AI-powered robo-advisory systems.
Abstract
The rapid development of financial technology (FinTech) has accelerated the integration of artificial intelligence (AI) into smart financial services. AI-driven technologies have significantly improved the efficiency, accuracy, and intelligence of financial decision-making processes. This study reviews and analyzes major AI applications in smart finance, including heterogeneous data fusion models for credit risk assessment, real-time intelligent algorithms for financial fraud detection, and AI-powered robo-advisory systems. A literature review and case analysis approach is adopted to evaluate the practical effectiveness of these technologies. The findings indicate that AI can substantially improve credit evaluation accuracy, enhance fraud detection capability, and support personalized investment management. Nevertheless, challenges related to data privacy, model explainability, and regulatory compliance remain significant barriers to large-scale deployment. Future developments are expected to focus on federated learning, explainable AI, and generative AI technologies. This study provides a comprehensive overview of current applications, challenges, and future directions of AI in smart finance.