Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)

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Research on Financial Crimes Detection based on Big Data Technology

Authors
Ran Xu1, *, Junhao Bao2
1Faculty of Law, Macau University of Science and Technology, Macau, China
2School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan, China
*Corresponding author. Email: 1348713498@qq.com
Corresponding Author
Ran Xu
Available Online 27 October 2023.
DOI
10.2991/978-94-6463-276-7_6How to use a DOI?
Keywords
Financial Crimes; Big Data; Crime Detection; Accuracy; Response Cost
Abstract

Financial crimes including fraud, money laundering, insider trading, pose significant challenges to the stability and integrity of global financial systems. Detecting and preventing these crimes is a complex task that requires sophisticated tools and technologies. Currently, there still leaks effective methods to precisely detect crimes, which can cause tremendous economic loss in the trading system. In this work, we explore the role of big data technology in detecting financial crimes. Initially, we discuss the core challenges in financial crime detection and how big data technology can address these issues, which includes the importance of data integration, data quality and real-time analysis in identifying suspicious patterns and anomalies indicative of financial crimes. Subsequently, we simulate the proposed framework and evaluate the benefits of implementing big data technology in financial crime detection with existing detection methods. From our extensive simulation results, we can significantly observe that our proposed method can detect financial crimes from enormous trading data with reasonable response costs and effective detection accuracy through comparing with existing identification models.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
27 October 2023
ISBN
10.2991/978-94-6463-276-7_6
ISSN
2667-128X
DOI
10.2991/978-94-6463-276-7_6How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ran Xu
AU  - Junhao Bao
PY  - 2023
DA  - 2023/10/27
TI  - Research on Financial Crimes Detection based on Big Data Technology
BT  - Proceedings of the 2023 4th International Conference on Big Data and Social Sciences (ICBDSS 2023)
PB  - Atlantis Press
SP  - 46
EP  - 52
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-276-7_6
DO  - 10.2991/978-94-6463-276-7_6
ID  - Xu2023
ER  -