Advanced fraud detection in financial systems: a comparative study of machine learning models on imbalanced data

Xiangting Shi; Yakang Zhang; Manning Yu; Jianan Chen

doi:10.1038/s41598-026-55224-2

Advanced fraud detection in financial systems: a comparative study of machine learning models on imbalanced data

X Xiangting Shi Y Yakang Zhang M Manning Yu J Jianan Chen (The Key Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology)

View Original

APA MLA Chicago BibTeX RIS

Article Details

Journal Scientific Reports

Volume / Issue Vol. 1, Issue 1

Published July 14, 2026

DOI 10.1038/s41598-026-55224-2

ISSN 2045-2322

Publisher Nature Portfolio

Journal Info

Scientific Reports

Nature Portfolio

ISSN: 2045-2322 Open Access Life Sciences

Authors (4)

X

Xiangting Shi

Y

Yakang Zhang

M

Manning Yu

J

Jianan Chen

The Key Laboratory of Computational Chemistry and Drug Design, State Key Laboratory of Chemical Oncogenomics, School of Chemical Biology and Biotechnology

Advanced fraud detection in financial systems: a comparative study of machine learning models on imbalanced data

Article Details

Journal Info

Authors (4)

Related Articles from this Journal

AI models of unstable flow exhibit hallucination

The MCAA-YOLO + XPBI integrated model provides a hybrid intelligent measurement method for predicting the body weight of Hu sheep

Application of iron nano-biofertilizers as a sustainable approach to enhance growth and micronutrient uptake in soybean

Adolescents’ status-dependent public and private conformity to prosocial and antisocial decisions in a public goods game

An explainable hierarchical capsule network framework for supporting expert sensory evaluation of herbal medicines with natural language generation