Detecting Fraudulent Bank Account Based on Convolutional Neural Network with Heterogeneous Data
Joint Authors
Lv, Fang
Wang, Wei
Wei, Yuliang
Sun, Yunxiao
Huang, Junheng
Wang, Bailing
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-25
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Detecting fraudulent accounts by using their transaction networks is helpful for proactively preventing illegal transactions in financial scenarios.
In this paper, three convolutional neural network models, i.e., NTD-CNN, TTD-CNN, and HDF-CNN, are created to identify whether a bank account is fraudulent.
The three models, same in model structure, are different in types of the input features.
Firstly, we embed the bank accounts’ historical trading records into a general directed and weighted transaction network.
And then, a DirectedWalk algorithm is proposed for learning an account’s network vector.
DirectedWalk learns social representations of a network’s vertices, by modeling a stream of directed and time-related trading paths.
The local topological feature, generating by accounts’ network vector, is taken as input of NTD-CNN, and TTD-CNN takes time series transaction feature as input.
Finally, the two kinds of heterogeneous data, being integrated into a novel feature matrix, are fed into HDF-CNN for classifying bank accounts.
The experimental results, conducted on a real bank transaction dataset, show the advantage of HDF-CNN over the existing methods.
American Psychological Association (APA)
Lv, Fang& Wang, Wei& Wei, Yuliang& Sun, Yunxiao& Huang, Junheng& Wang, Bailing. 2019. Detecting Fraudulent Bank Account Based on Convolutional Neural Network with Heterogeneous Data. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1195275
Modern Language Association (MLA)
Lv, Fang…[et al.]. Detecting Fraudulent Bank Account Based on Convolutional Neural Network with Heterogeneous Data. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1195275
American Medical Association (AMA)
Lv, Fang& Wang, Wei& Wei, Yuliang& Sun, Yunxiao& Huang, Junheng& Wang, Bailing. Detecting Fraudulent Bank Account Based on Convolutional Neural Network with Heterogeneous Data. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1195275
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1195275