Chapter 23: The Role of Artificial Intelligence in Improving the Quality of Financial Data

Financial data quality has dramatically improved through artificial intelligence (AI) progress, which presents revolutionary solutions to problems of accuracy, transparency, and efficiency. This research explores how AI is a fundamental tool for improving financial data integrity through machine learning technology, natural language processing, and robotic process automation. AI-driven error detection and real-time data validation reduce human involvement in financial tasks while reducing manual processing inconsistencies and biases. The study uses mixed-methods research by integrating quantitative investigations of AI-based data quality systems with qualitative case study examinations in the financial domain. Research outcomes demonstrate that AI achieves a 32% enhancement in data accuracy and increases processing speeds by 48%, alongside an 82% improvement in regulatory compliance. AI with blockchain technology creates unchangeable audit records and ensures accountability in financial reports. Current efforts have improved many areas, but critical issues like algorithmic opacity and data privacy still need resolution through adaptive regulatory frameworks. The research introduces explainable AI (XAI) and federated learning as potential solutions to tackle current ethical challenges in AI. AI achieves sustainable financial decision-making when technological advances work alongside human oversight. The study provides a novel AI-based framework that enhances financial data quality through automated processes and human professional judgment. The study reveals how AI can transform financial stability and presents recommendations for policymakers and bodies.