AI-ENABLED MANAGEMENT INFORMATION SYSTEMS FOR CREDIT AND MARKET RISK PREDICTION: EFFECTS ON ACCOUNTING DECISION QUALITY

• Md. Jobayer Ahmed

  Daffodil International University, Bangladesh

Objective: This study aims to examine the role of Artificial Intelligence (AI) in enhancing financial risk management and accounting decision-making, with a particular focus on credit and market risk prediction, efficiency of Management Information Systems (MIS), and the accuracy of financial reporting. Method: The study adopts a conceptual and analytical approach by synthesizing recent scholarly literature and real-world practices from financial institutions to evaluate the application of AI techniques, including machine learning and natural language processing, in risk assessment and accounting processes. Results: The findings indicate that AI-powered MIS significantly improves the speed, precision, and reliability of risk prediction and accounting operations by enabling real-time data analysis, anomaly detection, and automation of routine accounting tasks. These capabilities reduce human error, enhance regulatory compliance, and support more informed managerial decisions. However, the results also reveal critical challenges related to data quality, model transparency, algorithmic bias, governance structures, legal accountability, and high implementation costs, which may hinder effective adoption if not properly managed. Novelty: This study highlights the integrated perspective of AI-driven risk management and accounting while emphasizing the necessity of ethical governance frameworks and the future potential of combining AI with emerging technologies such as blockchain and the Internet of Things to build resilient and transparent financial systems.

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