Deep Learning Fraud Detection in Mobile Payment Transactions

• Author(s): Naveen Kamble; Praful S; Rohith V
• Paper ID: 1716911
• Page: 3208-3211
• Published Date: 27-04-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 10 April-2026

Abstract

With growing digital UPI payment platforms for online payment, concurrently there is rise in digital fraudulent activities which can cause financial loss for individuals, businesses, Govt entities. So to prevent such losses and digital fraudulent activities there is requirement of Deep learning models. Deep learning is nothing but a branch of Machine learning which uses neural network to learn large set of previously stored data and analyze real-time transactions to conclude the transactions as genuine or fraud and detect the suspicious activity. It inspects thoroughly advances in models, such as Artificial Neural Network [ANN], Recurrent Neural Network [RNN], Long-short term memory [LSTM], Gated recurrent units [GRU], and Auto-encoders. As a key volunteer, this study initiates Deep Learning-Sector-Governance [DLSG] framework. By incorporating above introduced models, this review offers practical counselling for researchers, industry practitioners working to avert fraud activities.

Keywords

Deep learning; Machine learning; ANN; RNN; LSTM; GRU; Auto-encoders; Fraud detection, UPI.

Citations

IRE Journals:
Naveen Kamble, Praful S, Rohith V "Deep Learning Fraud Detection in Mobile Payment Transactions" Iconic Research And Engineering Journals Volume 9 Issue 10 2026 Page 3208-3211 https://doi.org/10.64388/IREV9I10-1716911

IEEE:
Naveen Kamble, Praful S, Rohith V "Deep Learning Fraud Detection in Mobile Payment Transactions" Iconic Research And Engineering Journals, 9(10) https://doi.org/10.64388/IREV9I10-1716911