A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing

Yunus Korkmaz; Sadık Serçek; Mukaddes Korkmaz

doi:10.46460/ijiea.1789267

EN TR

A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing

Abstract

In accounting, auditing involves reviewing the financial statements and records of an organization by independent auditors in order to guarantee their precision and comply with relevant statutes and rules. Audits are typically conducted by external or internal auditors who review financial statements, assess internal controls, and verify the precision of financial data. The aim of audit is to provide confidence to stakeholders that the pecuniary data presented by the organization is reliable and trustworthy. In this work, role of the artificial intelligence (AI) was examined with a comprehensive literature review for auditing in accounting area. In technical aspect of this work, we built a fraudulent company detection system based on machine learning (ML) classification algorithms like Decision Tree (DT), Bagged Tree, Ensemble KNN (K-Nearest Neighbors), Linear Support Vector Machines (SVM) etc. Decision Tree and Bagged Tree reached AUC value of 1 which means that they are the perfect classifiers. The AUC values of 0.99, 0.99, 0.9998 and 0.9963 were obtained for Linear SVM, Logistic Regression, Subspace KNN and Naïve Bayes, respectively. The result proved that any machine learning based solution can help auditors to easily have an idea about the fraudulent companies before on-site auditing.

Keywords

Machine Learning , Suspicious Company , Decision Tree , Bibliometric Analysis , Accounting and Auditing

A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing

Öz

In accounting, auditing involves reviewing the financial statements and records of an organization by independent auditors in order to guarantee their precision and comply with relevant statutes and rules. Audits are typically conducted by external or internal auditors who review financial statements, assess internal controls, and verify the precision of financial data. The aim of audit is to provide confidence to stakeholders that the pecuniary data presented by the organization is reliable and trustworthy. In this work, role of the artificial intelligence (AI) was examined with a comprehensive literature review for auditing in accounting area. In technical aspect of this work, we built a fraudulent company detection system based on machine learning (ML) classification algorithms like Decision Tree (DT), Bagged Tree, Ensemble KNN (K-Nearest Neighbors), Linear Support Vector Machines (SVM) etc. Decision Tree and Bagged Tree reached AUC value of 1 which means that they are the perfect classifiers. The AUC values of 0.99, 0.99, 0.9998 and 0.9963 were obtained for Linear SVM, Logistic Regression, Subspace KNN and Naïve Bayes, respectively. The result proved that any machine learning based solution can help auditors to easily have an idea about the fraudulent companies before on-site auditing.

Anahtar Kelimeler

Machine Learning , Suspicious Company , Decision Tree , Bibliometric Analysis , Accounting and Auditing

Kaynakça

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Ayrıntılar

Birincil Dil

İngilizce

Konular

Bilgisayar Yazılımı , Yazılım Mühendisliği (Diğer)

Bölüm

Araştırma Makalesi

Yazarlar

Yunus Korkmaz ^*
0000-0002-6315-5750
Türkiye

Sadık Serçek
0000-0003-2429-320X
Türkiye

Mukaddes Korkmaz
0009-0005-6932-2205
Türkiye

Yayımlanma Tarihi

29 Aralık 2025

Gönderilme Tarihi

23 Eylül 2025

Kabul Tarihi

25 Kasım 2025

Yayımlandığı Sayı

Yıl 2025 Cilt: 9 Sayı: 2

DOI

https://doi.org/10.46460/ijiea.1789267

IZ

https://izlik.org/JA62FM89DM

APA

Korkmaz, Y., Serçek, S., & Korkmaz, M. (2025). A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing. International Journal of Innovative Engineering Applications, 9(2), 164-174. https://doi.org/10.46460/ijiea.1789267

AMA

1.Korkmaz Y, Serçek S, Korkmaz M. A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing. ijiea, IJIEA. 2025;9(2):164-174. doi:10.46460/ijiea.1789267

Chicago

Korkmaz, Yunus, Sadık Serçek, ve Mukaddes Korkmaz. 2025. “A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing”. International Journal of Innovative Engineering Applications 9 (2): 164-74. https://doi.org/10.46460/ijiea.1789267.

EndNote

Korkmaz Y, Serçek S, Korkmaz M (01 Aralık 2025) A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing. International Journal of Innovative Engineering Applications 9 2 164–174.

IEEE

[1]Y. Korkmaz, S. Serçek, ve M. Korkmaz, “A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing”, ijiea, IJIEA, c. 9, sy 2, ss. 164–174, Ara. 2025, doi: 10.46460/ijiea.1789267.

ISNAD

Korkmaz, Yunus - Serçek, Sadık - Korkmaz, Mukaddes. “A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing”. International Journal of Innovative Engineering Applications 9/2 (01 Aralık 2025): 164-174. https://doi.org/10.46460/ijiea.1789267.

JAMA

1.Korkmaz Y, Serçek S, Korkmaz M. A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing. ijiea, IJIEA. 2025;9:164–174.

MLA

Korkmaz, Yunus, vd. “A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing”. International Journal of Innovative Engineering Applications, c. 9, sy 2, Aralık 2025, ss. 164-7, doi:10.46460/ijiea.1789267.

Vancouver

1.Yunus Korkmaz, Sadık Serçek, Mukaddes Korkmaz. A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing. ijiea, IJIEA. 01 Aralık 2025;9(2):164-7. doi:10.46460/ijiea.1789267

A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing

Abstract

Keywords

A Suspicious Company Detection System Based on Machine Learning with a Bibliometric Analysis for Accounting and Auditing

Öz

Anahtar Kelimeler

Kaynakça

Ayrıntılar

Birincil Dil

Konular

Bölüm

Yazarlar

Yayımlanma Tarihi

Gönderilme Tarihi

Kabul Tarihi

Yayımlandığı Sayı

DOI

IZ

Kaynak Göster