A Systematic Literature Review: The Use of Artificial Intelligence and Machine Learning in Financial Risk Management and Predictive Analytics
Keywords:
Artificial Intelligence, Machine Learning, Financial Risk Management, Predictive Analytics, Systematic Literature Review, FintechAbstract
This systematic literature review explores the role of Artificial Intelligence (AI) and Machine Learning (ML) in financial risk management and predictive analytics by analyzing 20 peer-reviewed articles published between 2019 and 2025. From an initial pool of 131 articles, a rigorous screening process was conducted to ensure relevance and quality. The findings indicate that AI and ML have significantly enhanced the accuracy, speed, and adaptability of financial risk assessments, particularly in areas such as credit risk prediction, fraud detection, and market volatility forecasting. However, challenges such as lack of model transparency, limited implementation in real-world settings, and insufficient coverage of emerging markets remain prevalent. This review identifies future research opportunities including the development of explainable AI (XAI), alignment with regulatory frameworks, expansion into underexplored financial domains, and the creation of localized models for inclusive finance. Overall, AI and ML demonstrate transformative potential, but their effectiveness depends on responsible, context-aware, and interdisciplinary application
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