Prototype A Decision Support Framework for Fraud Detection in Accounting Information Systems

Abstract

This research focuses on developing, implementing, and validating a prototype decision support system (DSS) designed specifically for detecting fraud in accounting information systems (AIS). The prototype integrates advanced artificial intelligence (AI), data analytics, and expert-driven rule-based reasoning, structured to enhance internal control effectiveness and early fraud detection. Employing a quantitative research methodology, the prototype underwent rigorous simulation testing and statistical evaluation. Analytical techniques such as regression analysis were utilized to determine system effectiveness. Results indicate the DSS prototype significantly improves detection accuracy and auditor responsiveness, contributing practical insights for auditors, financial institutions, and regulatory bodies seeking to mitigate fraud through innovative technological solutions.