Enhancing Digital Wallet Payments through Data Analytics: A Study on Fraud Prevention and Personalized User Experience

Authors

  • Rahul Reddy Bandhela, RamMohan Reddy Kundavaram, Abhishake Reddy Onteddu

Keywords:

Digital wallet payments, fraud detection, user personalization, data analytics, anomaly detection, ensemble model, Isolation Forest, Local Outlier Factor, Long Short-Term Memory, machine learning.

Abstract

The rapid adoption of digital wallets has revolutionized consumer financial interactions, offering convenience and
facilitating the transition to cashless payments

References

Pu X, Chan FT, Chong AY, Niu B. The adoption of NFC-based mobile payment services: an empirical analysis of Apple Pay in China. International Journal of Mobile Communications. 2020;18(3):343-71.

Verkijika SF. An affective response model for understanding the acceptance of mobile payment systems. Electronic Commerce Research and Applications. 2020 Jan 1;39:100905.

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Published

2024-03-20

How to Cite

Rahul Reddy Bandhela, RamMohan Reddy Kundavaram, Abhishake Reddy Onteddu. (2024). Enhancing Digital Wallet Payments through Data Analytics: A Study on Fraud Prevention and Personalized User Experience. Journal of Computational Analysis and Applications (JoCAAA), 33(2), 1523–1535. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/3034

Issue

Vol. 33 No. 2 (2024): JOCAAA

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.