The Effectiveness of Artificial Intelligence In Enhancing Fraud Detection in Financial Systems

This paper examines the application of Artificial Intelligence (AI) in fraud detection within financial systems. It reviews previous studies to evaluate the effectiveness of AI-based methods compared with conventional rule-based approaches, as well as the key components and challenges involved in their implementation. The findings indicate that AI can improve the accuracy and efficiency of fraud detection, while factors such as data quality, model transparency, data privacy, system integration, regulatory requirements, and implementation costs remain important challenges.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-15
DOI
https://doi.org/10.5281/zenodo.22772371
Primary Topic
Imbalanced Data Classification Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

The Effectiveness of Artificial Intelligence In Enhancing Fraud Detection in Financial Systems

Jovan Widodo
Zenodo (CERN European Organization for Nuclear Research)
Imbalanced Data Classification Techniques
article

The Effectiveness of Artificial Intelligence In Enhancing Fraud Detection in Financial Systems

Jovan Widodo
article en

Abstract

This paper examines the application of Artificial Intelligence (AI) in fraud detection within financial systems. It reviews previous studies to evaluate the effectiveness of AI-based methods compared with conventional rule-based approaches, as well as the key components and challenges involved in their implementation. The findings indicate that AI can improve the accuracy and efficiency of fraud detection, while factors such as data quality, model transparency, data privacy, system integration, regulatory requirements, and implementation costs remain important challenges.

Zenodo (CERN European Organization for Nuclear Research)
Binus University (ID)
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Imbalanced Data Classification Techniques
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.

The Effectiveness of Artificial Intelligence In Enhancing Fraud Detection in Financial Systems — Jovan Widodo · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS