Location based FDS Framework

  • Authors

    • Jong Bae Kim
    • Myung Jin Bae
  • Fraud Detection System, Financial, Fintech, Location, GPS, Governance.
  • The FDS (Fraud Detection System) is a technological approach to prevent financial accidents by detecting abnormal behavior in financial transactions. In this paper, we present system components and considerations for efficient FDS construction and operation, and propose an optimized FDS operation framework based on IT governance. In addition, we propose a model that can improve the accuracy of abnormal transaction detection by using GPS information of user. This research is expected to be an operation model for Fintech based FDS that enables safe transactions without sacrificing the convenience of customers.



  • References

    1. [1] Gomber, P., Kauffman, J., Parker, C., Weber, W., On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services. Journal of Management Information Systems, Vol. 35 Issue 1 (2004), 220-265.

      [2] Aisha, A., Mohd, M., Anazida, Z., Fraud detection system: A survey. Journal of Network and Computer Applications., 68 (2016), 90-113.

      [3] Jungoh, P., Byungwook, J., A Study on Authentication Method for Secure Payment in Fintech Environment. The Journal of the Institute of Internet, Broadcasting and Communication (IIBC), Vol. 15, No. 4 (2015), 25-31.

      [4] Gozman, D., Liebenau, J., Mangan, J., The Innovation Mechanisms of Fintech Start-Ups: Insights from SWIFT’s Innotribe Competition. Journal of Management Information Systems, Vol. 35 Issue 1 (2018), 145-179.

      [5] Dhar, V., Stein, M., FinTech Platforms and Strategy: Integrating trust and automation in finance. Communications of the ACM, Vol. 60 Issue 10 (2017), 32-35.

      [6] Mooney, W. Jr., Fintech and Secured Transactions Systems of the Future. Law and Contemporary Problems, Vol. 81, Issue 1 (2018), 1-20.

      [7] Jayabrabu, R., Saravanan, V., Tamilselvi, J.J., A framework for fraud detection system in automated data mining using intelligent agent for better decision making process. 2014 International Conference on Green Computing Communication and Electrical Engineering (ICGCCEE), Mar (2014), 1-8.

      [8] GeumYeon J., InSeok K., A Study on the Institutional Limitations and Improvements for Electronic Financial Fraud Detection. The Journal of the Institute of Internet, Broadcasting and Communication (IIBC), Vol. 16, No. 6 (2016), 255-264.

      [9] Budi, S., Julita, H., Bambang, R., Laksono, T., System for detection of national healthcare insurance fraud based on computer application. Public Health of Indonesia, Vol 4, Issue 2 (2018), 46-56.

      [10] TaeEun, K., JungMi, L., SeonHo, H., GwangYong G., A Study of Finance Fraud Detection System Operation Framework. Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology, Vol.5, No.4 (2015), 9-17.

  • Downloads

  • How to Cite

    Bae Kim, J., & Jin Bae, M. (2018). Location based FDS Framework. International Journal of Engineering & Technology, 7(3.33), 72-77. https://doi.org/10.14419/ijet.v7i3.33.18527