EFFECT OF AI-POWERED FRAUD DETECTION SYSTEMS ON PROFITABILITY OF FINANCIAL INSTITUTIONS
Keywords:
AI Technologies, It Professionals, Return On Assets, Return On Equity, Fraud Detection, Financial Performance.Abstract
This study analyzes how AI-based fraud detection systems affect the profitability of financial institutions in Pakistan. Financial fraud is also getting sophisticated and widespread, and old methods of detecting fraud are becoming ineffective. Advanced solutions (AI technologies) are provided by machine learning and big data analytics, which detect fraudulent activities in real-time, enhance accuracy, and are less expensive. The study employs a quantitative approach, where 100 financial institutions such as 20 banks, 20 insurance companies as well as 60 others are involved, and all of them have implemented AI in their fraud detection systems. Primary data was obtained using the survey method after interviewing senior managers and the IT professionals and secondary data was acquired using the annual financial performance report and paid attention to the profitability indicators such as Return on Assets (ROA), Return on Equity (ROE) and Net Profit Margin. The results indicate that the adoption of AI is very beneficial in terms of profitability as it improves the accuracy of fraud detection, minimizes the risks associated with fraud, and reduces operational expenses. Additionally, there is a role of operational efficiency in connecting AI adoption with profitability whereby the more AI is adopted the more the operational costs are reduced. This study concludes that AI-based fraud detection software is a necessity to financial institutions in an effort to enhance profitability. Through automation of fraud detection, AI enhances operational efficiency, minimizes the costs of frauds, and enables institutions to grow without the corresponding rise in staffing and resources. The study indicates that the adoption of AI is important in improving financial performance, which gives institutions a competitive edge in the financial industry. Future research might further elaborate on such results by analyzing cross-country variations and long-term effects.
