BIG DATA IN FINANCIAL FRAUD DETECTION: INNOVATIVE APPROACHES

• Dr. Hassan Raza

  Department of Data Science, Institute of Business Administration (IBA), Karachi, Pakistan.

Financial fraud detection has become increasingly complex due to the rise of sophisticated fraudulent techniques and the massive volume of financial data. Big Data analytics offers innovative approaches to detecting and preventing financial fraud by analyzing vast datasets from multiple sources in real-time. This paper explores the various technologies and methods that leverage Big Data in financial fraud detection, including machine learning, predictive analytics, and data mining techniques, which can help financial institutions detect patterns and anomalies in large-scale financial data. By analyzing transaction records, behavioral patterns, and other relevant data, organizations can enhance the effectiveness of their fraud detection systems and improve their response times. The paper also discusses the challenges and ethical considerations involved in using Big Data for fraud detection in the financial sector.

Alesiani, D., & D’Amico, F. (2020). Big Data and Financial Fraud Detection: Challenges and Opportunities. International Journal of Computer Applications, 175(4), 12-18.

Angrishi, K., & Gupta, R. (2017). Financial Fraud Detection Using Big Data Technologies. Journal of Computer Science and Technology, 32(1), 29-39.

Baesens, B., Van Vlasselaer, V., & Verbeke, W. (2016). Fraud Detection Using Machine Learning and Big Data in the Financial Industry. Wiley & Sons.

Boussaid, I., & Mesfioui, M. (2019). Big Data and Predictive Analytics for Fraud Detection: Applications in the Financial Sector. Data Science and Engineering, 1(2), 101-113.

Christodoulou, E., & Manogaran, G. (2017). Data Mining Techniques for Fraud Detection in Financial Transactions. Journal of Financial Crime, 24(2), 167-180.

Gupta, H., & Saxena, S. (2018). Machine Learning for Financial Fraud Detection Using Big Data. Advances in Intelligent Systems and Computing, 656, 327-335.

Hodge, V. J., & Austin, S. (2018). Anomaly Detection for Financial Fraud: A Survey. Computing Research Repository, 32(4), 45-52.

Jin, S., & Zhang, X. (2020). Fraud Detection in Financial Transactions Using Big Data Analytics. International Journal of Data Mining & Knowledge Discovery, 34(7), 765-783.

Kotsiantis, S. B., & Pintelas, P. E. (2018). Artificial Intelligence and Big Data Applications in Financial Fraud Detection. Springer.

Lee, J. H., & Chen, H. (2019). Real-Time Financial Fraud Detection Using Big Data Technologies and Machine Learning Models. Journal of Financial Markets, 21(4), 58-66.

Liao, H., & Wang, X. (2020). Big Data in Financial Fraud Detection: A Review of Current Approaches. Journal of Financial Engineering, 12(3), 27-35.

Liu, Y., & Zhang, S. (2017). Big Data Analytics and Financial Fraud Prevention in Banking Sector. International Journal of Financial Studies, 5(1), 49-59.

Maimon, O., & Rokach, L. (2017). Data Mining and Decision Support for Financial Fraud Detection. Springer.

Martin, S., & Martin, C. (2018). Big Data for Financial Fraud Detection in Modern Financial Systems. Computer Science and Information Technology Journal, 16(3), 67-75.

Mounika, M., & Ramesh, P. (2019). Big Data-Based Approaches for Detecting Fraudulent Financial Transactions. Journal of Big Data Analytics, 25(2), 41-49.

Patro, M., & Singh, S. (2018). Financial Fraud Detection: A Survey of Big Data and Machine Learning Approaches. International Journal of Computational Intelligence and Applications, 17(2), 123-133.

Qiu, X., & Li, Z. (2021). Utilizing Big Data to Detect Financial Fraud in Real-Time Systems. Financial Technologies Journal, 29(5), 245-257.

Santimano, P., & Kiran, K. (2020). Innovative Approaches in Big Data for Financial Fraud Detection and Prevention. Journal of Financial Technology, 6(2), 101-115.

Tiwari, S., & Shukla, P. (2021). Leveraging Big Data Analytics for Financial Fraud Detection: A Comparative Study. International Journal of Artificial Intelligence and Data Mining, 3(4), 72-81.

Zhang, H., & Sun, M. (2019). An Overview of Big Data and Artificial Intelligence Techniques in Financial Fraud Detection. Journal of Computational Finance, 24(1), 22-34.

Ahmad, N. R. (2024). AI-enabled public governance in developing states: Service delivery gains, accountability risks, and a practical risk-based regulatory model. https://doi.org/10.52152/wja5db40

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