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Big Data in Financial Fraud Detection: A Machine Learning Approach

Year: 2025

Type: article

Abstract: This paper looks at how Big Data and Machine Learning can help detect financial fraud moreeffectively. Older fraud detection systems often miss new and complex fraud patterns. In this study,three different models—Logistic Regression, Random Forest, and Neural Network—were tested usingreal transaction data. The Neural Network gave the best results in catching fraud accurately. Thesefindings suggest that banks should start using smarter, AI-based systems to fight financial fraud.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15668194

Author: Shubhanker Srivastava

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6930889280

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