The Role of Artificial Intelligence in Fraud Detection and Prevention in Banking

In the evolving landscape of digital banking, the threat of financial fraud has become increasingly sophisticated and pervasive. This paper explores the pivotal role of Artificial Intelligence (AI) in detecting and preventing fraud within the banking sector. Traditional fraud detection systems, which rely on static rules and manual monitoring, are often insufficient against dynamic and rapidly evolving fraudulent techniques. AI-powered systems, leveraging machine learning, deep learning, and natural language processing, offer proactive, adaptive, and efficient solutions to mitigate financial risks. This study provides a comprehensive review of current AI technologies used in fraud detection, evaluates their effectiveness, discusses implementation challenges, and outlines future directions for AI integration in banking fraud prevention. By adopting AI, banks can enhance the security of their financial systems, ensure regulatory compliance, and improve customer trust and operational efficiency.

Authors

Publication Details

Journal
Journal of Information Systems Engineering & Management
Published
2025-05-22
DOI
https://doi.org/10.52783/jisem.v10i49s.10061
Citations
1
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
2.28
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Role of Artificial Intelligence in Fraud Detection and Prevention in Banking

Biswo Ranjan Mishra
1 citations
Journal of Information Systems Engineering & Management
FinTech, Crowdfunding, Digital Finance
2.28
article

The Role of Artificial Intelligence in Fraud Detection and Prevention in Banking

Biswo Ranjan Mishra
article en
1 citations

Abstract

In the evolving landscape of digital banking, the threat of financial fraud has become increasingly sophisticated and pervasive. This paper explores the pivotal role of Artificial Intelligence (AI) in detecting and preventing fraud within the banking sector. Traditional fraud detection systems, which rely on static rules and manual monitoring, are often insufficient against dynamic and rapidly evolving fraudulent techniques. AI-powered systems, leveraging machine learning, deep learning, and natural language processing, offer proactive, adaptive, and efficient solutions to mitigate financial risks. This study provides a comprehensive review of current AI technologies used in fraud detection, evaluates their effectiveness, discusses implementation challenges, and outlines future directions for AI integration in banking fraud prevention. By adopting AI, banks can enhance the security of their financial systems, ensure regulatory compliance, and improve customer trust and operational efficiency.

Journal of Information Systems Engineering & ManagementVol. 10(49s)
Openalex Percentile: Top 12%
FinTech, Crowdfunding, Digital Finance
2.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.