AI-DRIVEN SHARIAH COMPLIANCE DETECTION AND REAL-TIME MONITORING IN ISLAMIC FINANCE ACCOUNTING INFORMATION SYSTEMS - Suyatna, Nano; Nur'aeni, Nur'aeni; Firmansyah, Irman (Faculty of Economics and Business University of Mataram, 2025)
The research is motivated to develop an Artificial Intelligent-Based Accounting System (AI- AIS) using machine learning and natural language processing methods; isolation forest algorithm for anomaly detection, BERT classification framework to automize Shariah compliant monitoring in the financial statements. This study performs systematic review of literature as well development of functional prototyping. Key findings:(1)Detection of non-compliant transactions — riba, gharar detected in real-time 92% accurate over manual audits; (2)Shariah compliance screening for financial documents automated end to end; and, (3)Pre-validation on accounting entries prior to posting. This helps to shorten verification time from days to seconds and confirms compliance with AAOIFI regulations. The AIS uses cutting-edge AI technology that deals with some of the core issues in Islamic accounting, including but not limited to data integrity, reconciliation efficiency and transparency. It involves a system of accounting that uses the guiding principles laid out in Maqasid al-Shariah, eradicating financial risks based on balance. Further empirical and clinical attention to the integration of legacy systems, that their exegeses adjust themselves with contemporary Islamic jurisprudence on financial instruments; enabling a security design dabble compatible with off-the-shelf boards while developing an automated python script or the likes for identifying Shariah prohibitions may allow prevention.