Detection of Suspicious Transactions Based on Artificial Intelligence

Financial institutions and regulatory bodies have long sought effective methods to identifyand prevent illicit financial activities. With the exponential increase in digital transactionsand the sophistication of financial crimes, traditional rule-based systems are ofteninadequate to detect emerging patterns of fraudulent behavior.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-10
DOI
https://doi.org/10.5281/zenodo.14842115
Primary Topic
Clinical Laboratory Practices and Quality Control
Type
article
Field-Weighted Citation Impact
0.00
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article

Detection of Suspicious Transactions Based on Artificial Intelligence

Zenodo (CERN European Organization for Nuclear Research)
Clinical Laboratory Practices and Quality Control
article

Detection of Suspicious Transactions Based on Artificial Intelligence

article en

Abstract

Financial institutions and regulatory bodies have long sought effective methods to identifyand prevent illicit financial activities. With the exponential increase in digital transactionsand the sophistication of financial crimes, traditional rule-based systems are ofteninadequate to detect emerging patterns of fraudulent behavior.

Zenodo (CERN European Organization for Nuclear Research)
Peace, Justice and strong institutions
Openalex Percentile: Top 46%
Clinical Laboratory Practices and Quality Control
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Detection of Suspicious Transactions Based on Artificial Intelligence · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS