HOW AI AND MACHINE LEARNING IMPROVE FRAUD DETECTION IN FINANCIAL TRANSACTIONS.

Financial fraud poses significant risks to both institutions and consumers in the digital economy.Traditional detection methods often fail to keep pace with sophisticated fraudulent schemes.This paper examines the integration of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing fraud detection within financial transactions.By analysing vast datasets in real-time, AI-driven models can identify anomalous patterns indicative of fraud.The study reviews various AI methodologies, discusses their benefits and challenges, and explores future directions, including the integration of blockchain technology to improve data integrity and transparency.

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Publication Details

Journal
International Research Journal of Education and Technology (IRJET).
Published
2024-11-29
DOI
https://doi.org/10.70127/irjedt.vol.8.issue03.2403
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

HOW AI AND MACHINE LEARNING IMPROVE FRAUD DETECTION IN FINANCIAL TRANSACTIONS.

Shweta Vinayak Rasal
International Research Journal of Education and Technology (IRJET).
Imbalanced Data Classification Techniques
article

HOW AI AND MACHINE LEARNING IMPROVE FRAUD DETECTION IN FINANCIAL TRANSACTIONS.

Shweta Vinayak Rasal
article en

Abstract

Financial fraud poses significant risks to both institutions and consumers in the digital economy.Traditional detection methods often fail to keep pace with sophisticated fraudulent schemes.This paper examines the integration of Artificial Intelligence (AI) and Machine Learning (ML) in enhancing fraud detection within financial transactions.By analysing vast datasets in real-time, AI-driven models can identify anomalous patterns indicative of fraud.The study reviews various AI methodologies, discusses their benefits and challenges, and explores future directions, including the integration of blockchain technology to improve data integrity and transparency.

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