Proceedings of the International Conference on Multidisciplinary Research in Management and Economics (ICMRME 2025)

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The Role of Supervised Learning Algorithms in Fraud Detection for Financial Risk Management: A literature review

Authors
Hasna El Mekki1, *, Si Mohamed Bouaziz2
1PhD Candidate of Management Sciences, The Faculty of Legal, Economic and Social Sciences of Agadir, Agadir, Morocco
2Higher Education Professor, The Faculty of Legal, Economic and Social Sciences of Agadir, Agadir, Morocco
*Corresponding author. Email: hasnaelmekki@gmail.com
Corresponding Author
Hasna El Mekki
Available Online 17 November 2025.
DOI
10.2991/978-94-6463-892-9_2How to use a DOI?
Keywords
Fraud Detection; Financial Risk Management; Supervised Learning Algorithms
Abstract

Fraud detection is a major challenge in financial risk management, with direct implications for corporate stability and profitability. The application of supervised machine learning algorithms has significantly improved the efficiency of this process. This article examines the roles of various supervised learning methods, such as random forests (RF), support vector machines (SVMs) and artificial neural networks (ANN), on the identification and management of financial risks and the prevention of fraudulent activities. By mining a range of data and identifying complex patterns, these algorithms not only enable faster and more accurate fraud detection, but also significantly reduce financial losses. The article also discusses the challenges of integrating these models into existing systems, and highlights the potential for continuous improvement through machine learning. In conclusion, the adoption of these supervised learning algorithms for fraud detection represents an important step towards proactive and intelligent management, improving organizations’ ability to anticipate and manage risk.

Copyright
© 2025 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 International Conference on Multidisciplinary Research in Management and Economics (ICMRME 2025)
Series
Advances in Economics, Business and Management Research
Publication Date
17 November 2025
ISBN
978-94-6463-892-9
ISSN
2352-5428
DOI
10.2991/978-94-6463-892-9_2How to use a DOI?
Copyright
© 2025 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  - Hasna El Mekki
AU  - Si Mohamed Bouaziz
PY  - 2025
DA  - 2025/11/17
TI  - The Role of Supervised Learning Algorithms in Fraud Detection for Financial Risk Management: A literature review
BT  - Proceedings of the International Conference on Multidisciplinary Research in Management and Economics (ICMRME 2025)
PB  - Atlantis Press
SP  - 7
EP  - 19
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-892-9_2
DO  - 10.2991/978-94-6463-892-9_2
ID  - ElMekki2025
ER  -