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Neuro-Fuzzy Models for Electronic Banking Fraud Detection and Prevention: A Review of Recent Advances

Author

Listed:
  • Mohammed Usman

    (Department of Computer Science, Modibbo Adama University, Yola, Nigeria)

  • Etemi Joshua Garba

    (Department of Computer Science, Modibbo Adama University, Yola, Nigeria)

  • Usman Idris Ismai’il

    (Department of Computer Science, Federal University of Kashere, Nigeria)

Abstract

Online payments have evolved over the years. Today, more people are choosing electronic payments platforms over method traditional banking. From POS, mobile banking, to virtual banking services, there are lots of trends to facilitate seamless payments for customers. However, electronic fraud is affecting Nigeria’s financial system, costing the economy dearly and holding back the adoption of cashless technologies due to rise in fraudulent activities. This work focused on informing and helping the public to understand payment fraud issues occurring on various channels, as well as aid financial institutions with more effective fraud monitoring and preventive measures to combat the fraud. In this study, five feature of electronic banking transaction were selected and used to obtain universe of discourse, membership functions and their linguistic variables for the fuzzy system and are classified based on ANFIS to allow an E-banking fraud detection system to test and classify transactions as fraudulent or safe.

Suggested Citation

  • Mohammed Usman & Etemi Joshua Garba & Usman Idris Ismai’il, 2024. "Neuro-Fuzzy Models for Electronic Banking Fraud Detection and Prevention: A Review of Recent Advances," International Journal of Research and Innovation in Applied Science, International Journal of Research and Innovation in Applied Science (IJRIAS), vol. 9(7), pages 406-414, July.
    • Handle: RePEc:bjf:journl:v:9:y:2024:i:7:p:406-414
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