Work

Detection of Suspicious Transactions Based on Artificial Intelligence

Year: 2025

Type: article

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.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14842115

Author: O. Yoldashev,

Language: English

Topic: Imbalanced Data Classification Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Peace, justice, and strong institutions

Open Access status: green

OpenAlex ID: W6893216252

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