Artificial Intelligence and Machine Learning in Financial Services: A Systematic Literature Review

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have changed how financial services operate, improving areas like trading, credit assessments, fraud detection, and customer service. These technologies enhance efficiency and customer experience but raise concerns about fairness and regulations. This review looks at research on AI and ML in financial services, focusing on their use, performance, and regulatory challenges from 2018 to 2024. A search of academic databases found 86 relevant studies that analyzed technical implementation, performance, ethics, and market impacts. Results showed that ML in fraud detection can exceed 90% accuracy, and AI in credit scoring can lower prediction errors by 15-25%. Despite these advancements, challenges remain, especially in explainability, bias, and regulation. Successful adoption of AI and ML requires addressing these issues through responsible frameworks and governance structures.