The Impact Of Artificial Intelligence On Financial Reporting Accuracy And Fraud Detection: Evidence From Indian Banking Companies
Main Article Content
Abstract
Artificial Intelligence (AI) is a revolutionary technology in the banking industry that has dramatically affected financial reporting systems and fraud detection systems. This study analyzes the effect of AI on the accuracy of financial reporting and efficiency in fraud detection in Indian banking firms through a quantitative research methodology. A structured questionnaire was used to gather primary data on 80 banking professionals and conduct an analysis based on the statistical methods, including mean, standard deviation, weighted scores, correlation analysis, and ranking. The results indicate that AI is beneficial to financial reporting, by improving data consistency, error reduction, and enabling real-time processing, and enhancing fraud detection, using methods like pattern recognition, anomaly detection, and predictive analytics. The research also establishes some of the challenges such as expensive implementation, privacy of the data, and skills gaps, which influence the adoption of AI. In spite of these difficulties, the findings suggest that AI is critical in enhancing transparency, efficiency, and risk management in the banking systems. The research offers viable information to financial institutions and policymakers to facilitate the successful implementation of AI in the banking industry.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
References
Adhikari, P., Hamal, P., & Jnr, F. B. (2024). Artificial Intelligence in fraud detection: Revolutionizing financial security. International Journal of Science and Research Archive, 13(1), 1457-1472.
Aljunaid, S. K., Almheiri, S. J., Dawood, H., & Khan, M. A. (2025). Secure and transparent banking: Explainable AI-driven federated learning model for financial fraud detection. Journal of Risk and Financial Management, 18(4), 179.
Ansari, A., Valipour, H., & Salehi, H. (2025). The Impact of Artificial Intelligence Algorithms on Financial Fraud Detection and Prevention: The Moderating Role of Internal Control Systems. International Journal of Finance & Managerial Accounting, 12(47), 93-110.
Aziz, L. A. R., & Andriansyah, Y. (2023). The role artificial intelligence in modern banking: an exploration of AI-driven approaches for enhanced fraud prevention, risk management, and regulatory compliance. Reviews of contemporary business analytics, 6(1), 110-132.
Bhagat, N. (2024). Artificial intelligence challenges and its impact on detection and prevention of financial statement fraud: A theoretical study. In Demystifying the Dark Side of AI in Business (pp. 60-80). IGI Global Scientific Publishing.
Dwadasi, A. (2024). Artificial intelligence and machine learning in financial services: risk management and fraud detection. J. Electrical Systems, 20(6s), 1418-24.
Mohammadi, M., Yazdani, S., Khanmohammadi, M. H., & Maham, K. (2020). Financial reporting fraud detection: An analysis of data mining algorithms. International Journal of Finance & Managerial Accounting, 4(16), 1-12.
Mohanty, B., & Mishra, S. (2023). Role of artificial intelligence in financial fraud detection. Academy of marketing studies journal, 27(S4).
Narender, M., & Anand, A. J. (2025). Artificial Intelligence in Financial Fraud Detection. In Handbook of AI-Driven Threat Detection and Prevention (pp. 193-207). CRC Press.
Naseer, K., & Ahmed, H. N. (2025). Effectiveness and reliability of artificial intelligence in fraud detection: A mixed-method study on financial audit. Journal of Management and Informatics, 4(1), 706-722.
Patil, D. (2024). Artificial intelligence in financial services: Advancements in fraud detection, risk management, and algorithmic trading optimization. Risk Management, And Algorithmic Trading Optimization (November 20, 2024).
Raza, M., Qurashi, H., Haidar, A., & Raza, M. S. (2025). Artificial Intelligence in Auditing: Transforming Fraud Detection, Risk Assessment and Assurance Quality in Financial Reporting. Journal of Asian Development Studies, 14(3), 453-466.
Thakkar, H., Datta, S., Bhadra, P., Barot, H., & Jadav, J. (2025). Artificial intelligence and machine learning in fraud detection: A comprehensive bibliometric mapping of research trends and directions. Annals of Library and Information Studies, 72(2), 138-150.
Tiwari, R. (2023). The application of AI and machine learning in the financial industry and its effects on risk management and fraud detection. International Journal of Scientific Research In Engineering And Management, 7(1), 1-12.
Yaseen, H., & Al-Amarneh, A. A. (2025). Adoption of artificial intelligence-driven fraud detection in banking: The role of trust, transparency, and fairness perception in financial institutions in the United Arab Emirates and Qatar. Journal of Risk and Financial Management, 18(4), 217.