ONLINE PAYMENT FRAUD DETECTION MODEL USING MACHINE LEARNING

Abstract –As we all know that nowadays the demand and the use of the UPI i.e. Unified Payments Interface isincreasing so rapidly. Due to its high rise, some concerns and security issue related to UPI are raised.Many of the people will face the problem related to fake and fraud payments. So our study presentsthe detection of the fraud payments by utilizing the various machine learning algorithms. The systemproposed by us will integrates machine learning algorithms with rule-based methods to evaluate onrisk factors such as transaction amount, frequency, location, and behavioral anomalies. The frauddetection system follows four key phases which are user engagement, historical data analysis,continuous monitoring, and fraud prediction analysis. Keywords: UPI Transactions, Fraud Detection, Machine Learning, Real-Time Monitoring,Behavioral Analysis, Risk Assessment, Predictive Analysis.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-04-06
DOI
https://doi.org/10.5281/zenodo.15161951
Primary Topic
Statistical Methods and Applications
Type
article
Field-Weighted Citation Impact
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article

ONLINE PAYMENT FRAUD DETECTION MODEL USING MACHINE LEARNING

Zenodo (CERN European Organization for Nuclear Research)
Statistical Methods and Applications
article

ONLINE PAYMENT FRAUD DETECTION MODEL USING MACHINE LEARNING

article en

Abstract

Abstract –As we all know that nowadays the demand and the use of the UPI i.e. Unified Payments Interface isincreasing so rapidly. Due to its high rise, some concerns and security issue related to UPI are raised.Many of the people will face the problem related to fake and fraud payments. So our study presentsthe detection of the fraud payments by utilizing the various machine learning algorithms. The systemproposed by us will integrates machine learning algorithms with rule-based methods to evaluate onrisk factors such as transaction amount, frequency, location, and behavioral anomalies. The frauddetection system follows four key phases which are user engagement, historical data analysis,continuous monitoring, and fraud prediction analysis. Keywords: UPI Transactions, Fraud Detection, Machine Learning, Real-Time Monitoring,Behavioral Analysis, Risk Assessment, Predictive Analysis.

Zenodo (CERN European Organization for Nuclear Research)
Indian Numismatic, Historical and Cultural Research Foundation (IN)
Peace, Justice and strong institutions
Openalex Percentile: Top 53%
Statistical Methods and Applications
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