Determinasi Efektivitas Deteksi dan Pencegahan Fraud: Kajian Sistematis Multilevel Terintegrasi

Authors

  • Aan Andrianingsih Departemen Akuntansi FEB Universitas Diponegoro , Departemen Akuntansi FEB, Universitas Diponegoro
  • Abdul Rohman Departemen Akuntansi FEB, Universitas Diponegoro , Departemen Akuntansi FEB, Universitas Diponegoro

DOI:

https://doi.org/10.32534/jpk.v12i3.7193

Keywords:

Fraud Detection, Fraud Prevention, Audit Technology, Governance, Systematic Review

Abstract

Main Purpose - This study aims to synthesize academic literature on the determinants of effective fraud detection and prevention across multilevel dimensions.

Method - A Systematic Literature Review (SLR) was conducted using 34 peer-reviewed articles from the Scopus database published between 2016 and 2025. The study applied the PICO strategy and thematic synthesis across three systemic levels: technology, organization, and individual.

Main Findings - This study finds that anti-fraud effectiveness relies on the synergy of technology, organizational governance, and individual factors. The literature remains fragmented and geographically biased. The lack of longitudinal research is also a key limitation.

Theory and Practical Implications - This research emphasizes the importance of integrative and multilevel approaches to designing effective fraud risk management systems. It offers practical guidance for policymakers to combine technological innovation with strengthened governance and individual ethics.

Novelty - This study proposes a unified conceptual framework integrating technological, organizational, and individual determinants into a coherent fraud risk management system.

Downloads

Download data is not yet available.

References

ACFE. (2024). Occupational Fraud 2024: A Report to the Nations.

Ajzen, I. (2002). Perceived Behavioral Control, Self?Efficacy, Locus of Control, and the Theory of Planned Behavior. Journal of Applied Social Psychology, 32(4), 665–683. https://doi.org/10.1111/j.1559-1816.2002.tb00236.x

Al?dahasi, E. M., Alsheikh, R. K., Khan, F. A., & Jeon, G. (2025). Optimizing fraud detection in financial transactions with machine learning and imbalance mitigation. Expert Systems, 42(2). https://doi.org/10.1111/exsy.13682

Asare, S. K., & Wright, A. M. (2018). Field evidence about auditors’ experiences in consulting with forensic specialists. Behavioral Research in Accounting, 30(1), 1–25. https://doi.org/10.2308/bria-51787

Bansal, K., Paliwal, A. C., & Singh, A. K. (2025). Analysis of the benefits of artificial intelligence and human personality study on online fraud detection. International Journal of Law and Management, 67(2), 191–209. https://doi.org/10.1108/IJLMA-08-2023-0198

Banulescu-Radu, D., & Yankol-Schalck, M. (2024). Practical guideline to efficiently detect insurance fraud in the era of machine learning: A household insurance case. Journal of Risk and Insurance, 91(4), 867–913. https://doi.org/10.1111/jori.12452

Chen, L., Jia, N., Zhao, H., Kang, Y., Deng, J., & Ma, S. (2022). Refined analysis and a hierarchical multi-task learning approach for loan fraud detection. Journal of Management Science and Engineering, 7(4), 589–607. https://doi.org/10.1016/j.jmse.2022.06.001

Chersan, I.-C. (2009). How To Prevent Fraud. Research Papers in Economics, 1, 36–42. https://consensus.app/papers/how-to-prevent-fraud-chersan/d9cff4e9c7c15e3b82176cd398d392a0/

Chimonaki, C., Papadakis, S., & Lemonakis, C. (2023). Perspectives in fraud theories – A systematic review approach. F1000Research, 12, 933. https://doi.org/10.12688/f1000research.131896.1

Christian, N., Basri, Y. Z., & Arafah. (2019). Analysis of Fraud Triangle, Fraud Diamond and Fraud Pentagon Theory to Detecting Corporate Fraud in Indonesia. The International Journal of Business Management and Technology, 3(4). www.theijbmt.com

Cressey, D. R. (1953). Other people’s money; a study of the social psychology of embezzlement. In Other people’s money; a study of the social psychology of embezzlement. Free Press.

Crowe, H. L. (2011). Why The Fraud Triangle Is No Longer Enough.

Devi, P. V. S. (2024). Corporate Governance as a Detector of Financial Statement Fraud: Systematic Literature Review. Asia Pacific Fraud Journal, 9(1), 37–47. https://doi.org/10.21532/apfjournal.v9i1.342

Dewi, Y., Suharman, H., Koeswayo, P. S., & Tanzil, N. D. (2023a). Factors influencing the effectiveness of credit card fraud prevention in Indonesian issuing banks. Banks and Bank Systems, 18(3), 44–60. https://doi.org/10.21511/bbs.18(4).2023.05

Dewi, Y., Suharman, H., Koeswayo, P. S., & Tanzil, N. D. (2023b). What is the key determinant of the credit card fraud risk assessment in Indonesia? An idea for brainstorming. Banks and Bank Systems, 18(1), 26–37. https://doi.org/10.21511/bbs.18(1).2023.03

Ding, N., Ruan, X., Wang, H., & Liu, Y. (2025). Automobile Insurance Fraud Detection Based on PSO-XGBoost Model and Interpretable Machine Learning Method. Insurance: Mathematics and Economics, 120, 51–60. https://doi.org/10.1016/j.insmatheco.2024.11.006

Dong, W., Liao, S., & Zhang, Z. (2018). Leveraging Financial Social Media Data for Corporate Fraud Detection. Journal of Management Information Systems, 35(2), 461–487. https://doi.org/10.1080/07421222.2018.1451954

Eldawlatly, A., Alshehri, H., Alqahtani, A., Ahmad, A., Al-Dammas, F., & Marzouk, A. (2018). Appearance of Population, Intervention, Comparison, and Outcome as research question in the title of articles of three different anesthesia journals: A pilot study. Saudi Journal of Anaesthesia, 12(2), 283. https://doi.org/10.4103/sja.SJA_767_17

Elsayed, A. A. (2017). The Financial Statement Fraud Risk. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3039035

Garven, S. A., & Scarlata, A. N. (2021). An examination of internal audit function size: Evidence from u.s. government and nonprofit sectors. Current Issues in Auditing, 15(1), A38–A56. https://doi.org/10.2308/CIIA-2019-505

Gepp, A., Kumar, K., & Bhattacharya, S. (2021). Lifting the numbers game: identifying key input variables and a best-performing model to detect financial statement fraud. Accounting and Finance, 61(3), 4601–4638. https://doi.org/10.1111/acfi.12742

Halbouni, S. S., Obeid, N., & Garbou, A. (2016). Corporate governance and information technology in fraud prevention and detection: Evidence from the UAE. Managerial Auditing Journal, 31(6–7), 589–628. https://doi.org/10.1108/MAJ-02-2015-1163

Handoko, B. L., & Amelia, R. (2021). Implementation of Good Corporate Governance, Internal Audit, Whistle-Blowing System for Fraud Prevention in State-Owned Enterprise. The 2021 12th International Conference on E-Business, Management and Economics, 305–310. https://doi.org/10.1145/3481127.3481144

Hariyani, E., Supriono, S., Hanif, R. A., Silalahi, S. P., & Wiguna, M. (2024). Determinants influencing fraud detection: Role of internal auditors’ quality. Problems and Perspectives in Management, 22(2), 51–60. https://doi.org/10.21511/ppm.22(2).2024.05

Kambey, J. P., Peprah, W. K., Evinita, L. L., & Kewo, C. L. (2024). Predictors of Audit Quality: A Confirmatory Study. Quality - Access to Success, 25(203), 10–15. https://doi.org/10.47750/QAS/25.203.02

Lame, G. (2019). Systematic Literature Reviews: An Introduction. Proceedings of the Design Society: International Conference on Engineering Design, 1(1), 1633–1642. https://doi.org/10.1017/dsi.2019.169

Lonto, M. P., Sukoharsono, E. G., Baridwan, Z., & Prihatiningtias, Y. W. (2023). The Effectiveness of Internal Audit for Fraud Prevention. Australasian Accounting, Business and Finance Journal, 17(3), 171–190. https://doi.org/10.14453/aabfj.v17i3.11

Mandal, A., & S, A. (2025). Preventing financial statement fraud in the corporate sector: insights from auditors. Journal of Financial Reporting and Accounting, 23(1), 56–80. https://doi.org/10.1108/JFRA-02-2023-0101

Mansour, A. Z., Ahmi, A., & Popoola, O. M. J. (2020). The personality factor of conscientiousness on skills requirement and fraud risk assessment performance. International Journal of Financial Research, 11(2). https://doi.org/10.5430/ijfr.v11n2p405

Mock, T. J., Srivastava, R. P., & Wright, A. M. (2017). Fraud risk assessment using the fraud risk model as a decision aid. Journal of Emerging Technologies in Accounting, 14(1), 37–56. https://doi.org/10.2308/jeta-51724

Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015). Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement. Systematic Reviews, 4(1), 1. https://doi.org/10.1186/2046-4053-4-1

Musunuru, K. (2025). Big data analytics for financial auditing practices: Identification of conceptual patterns, implications and challenges using text mining | Análisis de big data para prácticas de auditoría financiera: identificación de patrones conceptuales, implicaciones. Contaduria y Administracion, 70(2), 184–219. https://doi.org/10.22201/fca.24488410e.2025.5283

Neogi, A., Mukhopadhyay, D., Jaiswal, A., Kumar, A., & Misra, B. (2024). Fraud Detection In Ethereum Transactions: A Machine Learning Approach. 2024 1st International Conference on Advanced Computing and Emerging Technologies (ACET), 1–7. https://doi.org/10.1109/ACET61898.2024.10729947

Nguyen, T. Q., Truong, T. H., Tran, M. D., Phung, V. H., Nguyen, T. L., & Tran, B. M. (2024). Determinants Influencing The Effectiveness of Internal Auditing And The Responsibility of Auditors In Fraud Detection In An Emerging Country. Journal of Governance and Regulation, 13(1 Special), 310–321. https://doi.org/10.22495/jgrv13i1siart5

Nindito, M., Avianti, I., Koeswayo, P. S., & Tanzil, N. D. (2025). Guardians of integrity: Exploring the role of corporate governance in preventing financial statement fraud. Journal of Governance and Regulation, 14(1), 109–118. https://doi.org/10.22495/jgrv14i1art10

Paganou, S., Antoniadis, I., Zournatzidou, G., & Sklavos, G. (2024). Investigating the Link among Corruption, Corporate Governance and Corporate Performance in Family Businesses: A Future Research Agenda. Administrative Sciences, 14(7). https://doi.org/10.3390/admsci14070139

Patel, S., Pandey, M., & D, R. (2024). Fraud Detection in Financial Transactions: A Machine Learning Approach. 2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM), 1–8. https://doi.org/10.1109/ICONSTEM60960.2024.10568903

Permatasari, D. (2021). Fraud Pentagon Sebagai Alat Pendeteksi Financial Statement Fraud: Literatur Review. Jurnal Ilmiah Mahasiswa Ekonomi Akuntansi (JIMEKA), 6(4), 1.

Pourhabibi, T., Ong, K.-L., Kam, B. H., & Boo, Y. L. (2020). Fraud detection: A systematic literature review of graph-based anomaly detection approaches. Decision Support Systems, 133. https://doi.org/10.1016/j.dss.2020.113303

Pratiwi, M. T., & Triyanto, D. N. (2022). Fraud Financial Statements In Pentagon’s Fraud Perspective (Study on the Mining Sector Listed on the Indonesia Stock Exchange 2016 – 2020 Period). JAF- Journal of Accounting and Finance, 6(2), 113. https://doi.org/10.25124/jaf.v6i2.5453

Ramesh, S., T M, S., & Mohana. (2024). Analysis of Credit Card Fraudulent Transactions Using Machine Learning and Artificial Intelligence. 2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI), 1226–1231. https://doi.org/10.1109/ICoICI62503.2024.10696309

Rezaee, Z., & Riley, R. (2009). Financial Statement Fraud Prevention and Detection.

Saini, A. K. (2023). The Role of Corporate Governance in Preventing Financial Fraud and Misconduct: An Empirical Study. International Journal of Early Childhood Special Education. https://doi.org/10.48047/intjecse/v14i5.1150

Sari, K. K. (2024). Whistleblowing System: The Effective Solution to Prevent Financial Accounting Fraud? Owner, 8(2), 1746–1758. https://doi.org/10.33395/owner.v8i2.2316

Soepriyanto, G., Meiryani, M., & Modjo, M. I. (2021). Theory and Factors Influencing Fraud in Financial Statements: A Systematic Literature Review. 2021 The 6th International Conference on E-Business and Mobile Commerce, 75–82. https://doi.org/10.1145/3472349.3472359

Soltani, M., Kythreotis, A., & Roshanpoor, A. (2024). The moderate role of national culture and prosperity index on the effectiveness of the fraud triangle to prevent financial statement fraud: a cross-country meta-analysis approach. International Journal of Accounting, Auditing and Performance Evaluation, 20(3–4), 251–290. https://doi.org/10.1504/IJAAPE.2024.138486

Soni, L., & Mangala, D. (2025). Preventing and detecting internal fraud risk: a critical analysis of the anti-fraud tools used by the Indian banking industry. Journal of Money Laundering Control, 28(2), 424–441. https://doi.org/10.1108/JMLC-11-2024-0193

Srinivasan, S., & Kamalakannan, T. (2018). Multi Criteria Decision Making in Financial Risk Management with a Multi-objective Genetic Algorithm. Computational Economics, 52(2), 443–457. https://doi.org/10.1007/s10614-017-9683-7

Sun, Y., Zeng, X., Xu, Y., Yue, H., & Yu, X. (2024). An intelligent detecting model for financial frauds in Chinese A-share market. Economics and Politics, 36(2), 1110–1136. https://doi.org/10.1111/ecpo.12283

Supriadi, T., Tjakrawala, K., Suryadnyana, N. A., Sjam, J. M. E., & Marota, R. (2025). Fraud Prevention In The Public Sector: The Role of Internal Audit. Ikonomicheski Izsledvania, 34(3), 170–183.

Suwandi Tjeng, P. (2023). How Does Corporate Governance Influence Fraud Practices? International Journal of Economics, Business and Management Research, 07(03), 13–29. https://doi.org/10.51505/IJEBMR.2023.7302

Vandervorst, F., Verbeke, W., & Verdonck, T. (2022). Data misrepresentation detection for insurance underwriting fraud prevention. Decision Support Systems, 159. https://doi.org/10.1016/j.dss.2022.113798

Vousinas, G. L. (2019). Advancing theory of fraud: the S.C.O.R.E. model. Journal of Financial Crime, 26(1), 372–381. https://doi.org/10.1108/JFC-12-2017-0128

Wolfe, D. T., & Hermanson, D. R. (2004). The Fraud Diamond: Considering the Four Elements of Fraud. https://digitalcommons.kennesaw.edu/facpubs

Yazid, H., Wiyantoro, L. S., Ismail, T., & Ismawati, I. (2025). Performance determinants of higher education institutions and the mediating role of quality culture: internal auditors’ perspectives. Cogent Business and Management, 12(1). https://doi.org/10.1080/23311975.2025.2455537

Zhao, D., Wang, Z., Schweizer-Gamborino, F., & Sornette, D. (2025). Polytope Fraud Theory. International Review of Financial Analysis, 97. https://doi.org/10.1016/j.irfa.2024.103734

Downloads

Published

2025-07-22

How to Cite

Determinasi Efektivitas Deteksi dan Pencegahan Fraud: Kajian Sistematis Multilevel Terintegrasi. (2025). Jurnal Proaksi, 12(3), 378-395. https://doi.org/10.32534/jpk.v12i3.7193

Most read articles by the same author(s)