Support Vector Machines: An Inclusive Survey in Financial Fraud Detection

Ermir Balliu; Bilal Saoud; Ibraheem Shayea; Timur Grigoryev

doi:10.1109/SNPD65828.2025.11488171

Support Vector Machines: An Inclusive Survey in Financial Fraud Detection

Ermir Balliu
, Bilal Saoud
, Ibraheem Shayea
, Timur Grigoryev

Faculty of Electrical and Electronics

Istanbul Technical University
Akli Mohand Oulhadj University of Bouira
Astana IT University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In the financial industry, using of several Machine Learning (ML) algorithms and artificial intelligence (AI) models has simplified the solution and detection of main problems related to its wide landscape. One of the most broadly used techniques of ML is Support Vector Machine (SVM) which owns its specific algorithms appropriated to detect frauds in financial applications. The reason why it is widely used in this field is that it can work well with High Dimensional Data (HDD) in applications where the number of features is greater than number of observations. Also, this technique is less susceptible to overfitting of HDD which makes it suitable for use in these cases.

Original language	English
Title of host publication	Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer
Editors	Hyun Yoe, Ha Jin Hwang, Meonghun Lee, Rackwoo Kim, Ryugap Lim, Sungtaek Lee, Seaeul Kim, Simon Xu, Miguel Garcia-Ruiz, Wenyin Feng, A B M Bodrul Alam, Randy Lin, Ajmery Sultana, Faria Khandaker, Mahreen Nasir, Ken Higuchi, Shinichiro Mori, Teruhisa Hochin
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331512583
DOIs	https://doi.org/10.1109/SNPD65828.2025.11488171
Publication status	Published - 2025
Event	29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer - Busa, Korea, Republic of Duration: 25 Jun 2025 → 27 Jun 2025

Publication series

Name	Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer

Conference

Conference	29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer
Country/Territory	Korea, Republic of
City	Busa
Period	25/06/25 → 27/06/25

Bibliographical note

Publisher Copyright:
©2025 IEEE.

Keywords

AI
financial applications
fraud detection
HDD
ML
overfitting
SVM

Access to Document

10.1109/SNPD65828.2025.11488171

Cite this

Balliu, E., Saoud, B., Shayea, I., & Grigoryev, T. (2025). Support Vector Machines: An Inclusive Survey in Financial Fraud Detection. In H. Yoe, H. J. Hwang, M. Lee, R. Kim, R. Lim, S. Lee, S. Kim, S. Xu, M. Garcia-Ruiz, W. Feng, A. B. M. B. Alam, R. Lin, A. Sultana, F. Khandaker, M. Nasir, K. Higuchi, S. Mori, & T. Hochin (Eds.), Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer (Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SNPD65828.2025.11488171

Balliu, Ermir ; Saoud, Bilal ; Shayea, Ibraheem et al. / Support Vector Machines : An Inclusive Survey in Financial Fraud Detection. Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer. editor / Hyun Yoe ; Ha Jin Hwang ; Meonghun Lee ; Rackwoo Kim ; Ryugap Lim ; Sungtaek Lee ; Seaeul Kim ; Simon Xu ; Miguel Garcia-Ruiz ; Wenyin Feng ; A B M Bodrul Alam ; Randy Lin ; Ajmery Sultana ; Faria Khandaker ; Mahreen Nasir ; Ken Higuchi ; Shinichiro Mori ; Teruhisa Hochin. Institute of Electrical and Electronics Engineers Inc., 2025. (Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer).

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abstract = "In the financial industry, using of several Machine Learning (ML) algorithms and artificial intelligence (AI) models has simplified the solution and detection of main problems related to its wide landscape. One of the most broadly used techniques of ML is Support Vector Machine (SVM) which owns its specific algorithms appropriated to detect frauds in financial applications. The reason why it is widely used in this field is that it can work well with High Dimensional Data (HDD) in applications where the number of features is greater than number of observations. Also, this technique is less susceptible to overfitting of HDD which makes it suitable for use in these cases.",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Balliu, E, Saoud, B, Shayea, I & Grigoryev, T 2025, Support Vector Machines: An Inclusive Survey in Financial Fraud Detection. in H Yoe, HJ Hwang, M Lee, R Kim, R Lim, S Lee, S Kim, S Xu, M Garcia-Ruiz, W Feng, ABMB Alam, R Lin, A Sultana, F Khandaker, M Nasir, K Higuchi, S Mori & T Hochin (eds), Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer. Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer, Institute of Electrical and Electronics Engineers Inc., 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer, Busa, Korea, Republic of, 25/06/25. https://doi.org/10.1109/SNPD65828.2025.11488171

Support Vector Machines: An Inclusive Survey in Financial Fraud Detection. / Balliu, Ermir; Saoud, Bilal; Shayea, Ibraheem et al.
Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer. ed. / Hyun Yoe; Ha Jin Hwang; Meonghun Lee; Rackwoo Kim; Ryugap Lim; Sungtaek Lee; Seaeul Kim; Simon Xu; Miguel Garcia-Ruiz; Wenyin Feng; A B M Bodrul Alam; Randy Lin; Ajmery Sultana; Faria Khandaker; Mahreen Nasir; Ken Higuchi; Shinichiro Mori; Teruhisa Hochin. Institute of Electrical and Electronics Engineers Inc., 2025. (Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Support Vector Machines

T2 - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer

AU - Balliu, Ermir

AU - Saoud, Bilal

AU - Shayea, Ibraheem

AU - Grigoryev, Timur

PY - 2025

Y1 - 2025

N2 - In the financial industry, using of several Machine Learning (ML) algorithms and artificial intelligence (AI) models has simplified the solution and detection of main problems related to its wide landscape. One of the most broadly used techniques of ML is Support Vector Machine (SVM) which owns its specific algorithms appropriated to detect frauds in financial applications. The reason why it is widely used in this field is that it can work well with High Dimensional Data (HDD) in applications where the number of features is greater than number of observations. Also, this technique is less susceptible to overfitting of HDD which makes it suitable for use in these cases.

AB - In the financial industry, using of several Machine Learning (ML) algorithms and artificial intelligence (AI) models has simplified the solution and detection of main problems related to its wide landscape. One of the most broadly used techniques of ML is Support Vector Machine (SVM) which owns its specific algorithms appropriated to detect frauds in financial applications. The reason why it is widely used in this field is that it can work well with High Dimensional Data (HDD) in applications where the number of features is greater than number of observations. Also, this technique is less susceptible to overfitting of HDD which makes it suitable for use in these cases.

KW - AI

KW - financial applications

KW - fraud detection

KW - HDD

KW - ML

KW - overfitting

KW - SVM

UR - https://www.scopus.com/pages/publications/105037106953

U2 - 10.1109/SNPD65828.2025.11488171

DO - 10.1109/SNPD65828.2025.11488171

M3 - Conference contribution

AN - SCOPUS:105037106953

T3 - Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer

BT - Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer

A2 - Yoe, Hyun

A2 - Hwang, Ha Jin

A2 - Lee, Meonghun

A2 - Kim, Rackwoo

A2 - Lim, Ryugap

A2 - Lee, Sungtaek

A2 - Kim, Seaeul

A2 - Xu, Simon

A2 - Garcia-Ruiz, Miguel

A2 - Feng, Wenyin

A2 - Alam, A B M Bodrul

A2 - Lin, Randy

A2 - Sultana, Ajmery

A2 - Khandaker, Faria

A2 - Nasir, Mahreen

A2 - Higuchi, Ken

A2 - Mori, Shinichiro

A2 - Hochin, Teruhisa

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 25 June 2025 through 27 June 2025

ER -

Balliu E, Saoud B, Shayea I, Grigoryev T. Support Vector Machines: An Inclusive Survey in Financial Fraud Detection. In Yoe H, Hwang HJ, Lee M, Kim R, Lim R, Lee S, Kim S, Xu S, Garcia-Ruiz M, Feng W, Alam ABMB, Lin R, Sultana A, Khandaker F, Nasir M, Higuchi K, Mori S, Hochin T, editors, Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer. Institute of Electrical and Electronics Engineers Inc. 2025. (Proceedings - 29th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2025-Summer). doi: 10.1109/SNPD65828.2025.11488171

Support Vector Machines: An Inclusive Survey in Financial Fraud Detection

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Bibliographical note

Keywords

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