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Proceedings of Data Analytics and Management pp 403–414Cite as

AI-Driven Fraud Detection and Mitigation in e-Commerce Transactions

Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT,volume 90)

Abstract

Digital technology has created new channels of digital transaction for e-Commerce and financial services distribution companies. The COVID-19 has intensified the adoption of digital transactions. With increased load, digital transactions have become more vulnerable to frauds and have created a lucrative avenue for fraudsters. Digital transactions pose a significant challenge to enterprises and customers for having secure business and financial transactions. To enhance the ease and convenience of the customers and business enterprises, the e-Commerce and financial service providers are deploying sophisticated tools that employ data analytics, AI and machine learning techniques. However, such tools are susceptible to compromise and challenging to enterprises and customers for having secure business and financial transactions. In this paper, we present the issues and challenges in identifying spurious online payments and detecting fraud in e-Commerce transactions. We also present the AI, and data analytics techniques are employed for the detection, prevention and control of online frauds in e-Commerce and financial transactions.

Keywords

  • Digital transaction
  • Online payments
  • Fraud detection
  • e-Commerce
  • Fraud mitigation

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Notes

  1. 1.

    https://www.digitalindia.gov.in/.

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Author information

Authors and Affiliations

  1. DCS, Jamia Millia Islamia, SIO and Scientist ‘F’, NIC, New Delhi, India

    Iqbal Hasan & SAM Rizvi

Authors
  1. Iqbal Hasan
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  2. SAM Rizvi
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Corresponding author

Correspondence to Iqbal Hasan .

Editor information

Editors and Affiliations

  1. Maharaja Agrasen Institute of Technology, New Delhi, India

    Deepak Gupta

  2. Jan Wyzykowski University, Polkowice, Poland

    Prof. Zdzislaw Polkowski

  3. Maharaja Agrasen Institute of Technology, New Delhi, India

    Ashish Khanna

  4. Rajnagar Mahavidyalaya, Birbhum, West Bengal, India

    Dr. Siddhartha Bhattacharyya

  5. Tijuana Institute of Technology, Tijuana, Mexico

    Oscar Castillo

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Cite this paper

Hasan, I., Rizvi, S. (2022). AI-Driven Fraud Detection and Mitigation in e-Commerce Transactions. In: Gupta, D., Polkowski, Z., Khanna, A., Bhattacharyya, S., Castillo, O. (eds) Proceedings of Data Analytics and Management . Lecture Notes on Data Engineering and Communications Technologies, vol 90. Springer, Singapore. https://doi.org/10.1007/978-981-16-6289-8_34

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