Extending the Fraud Diamond Theory: An Adaptive Framework for Preventing Customer-initiated Fraud in the Digital Banking Ecosystem

Ali Maskur, Ignatius Hari Santoso

Abstract


The rapid expansion of digital banking ecosystem has transformed financial service accessibility while simultaneously creating new opportunities for customer-initiated fraud. Compared to conventional banking systems, digital platforms present unique vulnerabilities arising from technological complexity, remote transaction, and reduced direct oversight. Although the Fraud Diamond Theory has been widely used to explain fraudulent behavior through pressure, opportunity, rationalization and capability, its applicability in customer-driven fraud within digital environment remains underexplored. This study aims to extend the Fraud Diamond Theory by introducing perceived severity as an adaptive construct to explain customer-initiated fraud intention. A mixed-method approach is employed using two sequential stages, which is in-depth interview and partial least square method to empirically test the new construct using 111 digital banking users. The findings reveal that financial pressure, rationalization, and perceived severity significantly influence customer-initiated fraud intention, meanwhile, perceived opportunity and capability are found to have no significant effect. This study contributes theoretically by extending Fraud Diamond Theory through the inclusion of deterrence-oriented perspective. Practically, the findings suggest that financial institution should complement technological security measures with behavioral interventions, user education and communication strategies emphasizing the consequences of fraudulent actions.

Keywords


fraud diamond theory; customer-initiated fraud intention; digital banking; perceived severity; digital banking

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References


Abdullahi, M., & Mansor, N. (2018). Fraud triangle theory and fraud diamond theory. International Journal of Academic Research ini Accounting, Finance and Management Science, 8(3), 106-112, https://doi.org/10.6007/IJARAFMS/v8-i3/4543

Aghghaleh, S.F., Mohamed, Z.M., & Rahmat, M.M. (2016). Detecting financial statement frauds in Malaysia: Comparing the abilities of Beneish and Dechow models. Asian Journal of Accounting and Governance, 7, 57-65, https://doi.org/10.17576/AJAG-2016-07-06

Alzoubi, E.S.S. (2018). Audit committee, internal audit function and earnings management. Journal of Applied Accounting Research, 19(3), 398-414, https://doi.org/10.1108/JAAR-06-2017-0062

Bada, M., & Nurse, J.R.C. (2019). Developing cybersecurity education and awareness programmes for small-medium-sized enterprises. Information & Computer Security, 27(3), 393-410, https://doi.org/10.1108/ICS-07-2018-0080

Bank Indonesia. (2023). Laporan Sistem Pembayaran Indonesia 2023. Bank Indonesia, https://www.bi.go.id/id/publikasi/laporan/Pages/Laporan-Sistem-Pembayaran-Indonesia-2023.aspx

Barbaranelli, C., Farnese, M.L., & Chirumbolo, A. (2018). Moral disengagement and unethical behavior. Frontiers in Psychology, 9, 1-12, https://doi.org/10.3389/fpsyg.2018.00001

Button, M., & Cross, C. (2017). Technology and fraud: The fraud justice network and the challenge of fraud investigation. Journal of Financial Crime, 24(4), 562-577, https://doi.org/10.1108/JFC-06-2016-0040

Cheng, L., Li, Y., Li, W., Holm, E., & Zhai, Q. (2017). Understanding the violation of information security policy: an Integrated model based on social control and deterrence theory. Computers & Security, 68, 1-14, https://doi.org/10.1016/j.cose.2017.04.003

Crossler, R.E., Belanger, F., & Ormond, D. (2017). The quest for complete security: an Empirical analysis. Computer & Security, 73, 1-16, https://doi.org/10.1016/j.cose.2017.10.001

Dodel, M., & Mesch, G. (2018). Cyber-victimization preventive behavior. Computers in Human behavior, 83, 1-9, https://doi.org/10.1016/j.chb.2018.01.012

Dorminey, J.W., Fleming, A.S., Kranacher, M.J., & Riley, R.A. (2018). The evolution of fraud theory. Issues in Accounting Education, 33(1), 1-15, https://doi.org/10.2308/iace-52104

Free, C. (2015). Looking through the fraud triangle : a Review and call for new directions. Meditari Accountancy Research, 23(2), 175-196, https://doi.org/10.1108/MEDAR-02-2015-0009

Guest, G., Namey, E., & Mitchell, M. (2017). Collecting qualitative data: a field manual for applied research. SAGE Publications.

Hadlington, L. (2017). Human factors in cybersecurity. Computers in Human Behavior, 69, 1-6, https://doi.org/10.1016/j.chb.2016.11.027

Hair, J.F., Hult, G.T.M., Ringle, C.M., & Sarstedt, M. (2022). A primer on partial least square structural equation modeling (PLS-SEM) 3rd edition. SAGE Publication_

Hair, J.F. (2021). Partial least square structural equation modeling. Handbook of Market Research, Springer, https://doi.org/10.1007/978-3-319-05542-8_15-2

Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135, https://doi.org/10.1007/s11747-014-0403-8

Hu, Q., Xu, Z., Dinev, T., & Ling, H. (2019). Does deterrence work in reducing information security policy abuse? Information & Management, 56(70, 103-115, https://doi.org/10.1016/j.im.2019.02.005

Ifinedo, P. (2018). Determinants of employee’s information system security policy compliance. Information & Computer Security, 26(3), 289-310, https://doi.org/10.1108/ICS-08-2017-0057

Ifinedo, P. (2019). The effect of deterrence factors on employees’ information security policy compliance intentions. Information System Frontiers, 21(2), 413-432, https://doi.org/10.1007/s10796-017-9801-1

Kassem, R., & Higson, A.W. (2016). External auditors and corporate corruption: Implications for external audit regulators. Current Issues in Auditing, 10(1), 1-10, https://doi.org/10.2308/ciia-51391

Kou, Y., Shi, Y., Wang, Z. (2021). Machine learning methods for fraud detection: a review. Decision Support Systems, 50(3), 1-12, https://doi.org/10.1016/j.dss.2020.113513

Leukfeldt, E.R. (2017). Phising for suitable targets in the Netherlands: Routine activity theory and phisinig victimization. Cyberpsychology Behavior and Social Networking, 20(3), 183-188, https://doi.org/10.1089/cyber.2016.0556

Levi, M., & Smith, R.G. (2021). Fraud and its relationship to pandemics and economics crises. Journal of Financial Crime, 28(3), 801-815, https://doi.org/10.1108/JFC-09-2020-0185

Maskur, A., & Santoso, I.H. (2025). Intergenerational insight of fraud intention in digital banking: What makes customers go rogue? Jurnal Manajemen, 22(2), 107-133, https://doi.org/10.25170/jm.v22i2.6735

Moore, C., & Gino, F. (2017). Ethically adrift: How others pull our moral compass. Harvard Business Review, https://doi.org/10.2139/ssrn.2596303

Nawawi, A., & Salin, A.S.A.P. (2018). Internal control and employees occupational fraud on expenditure claims. Journal of Financial Crime, 25(3), 891-906, https://doi.org/10.1108/JFC-07-2017-0067

Nurunnabi, M., & Nurunnabi, M. (2020). Fraud and governance in digital environments. journal of Financial Crima, 27(4), 1021-1038, https://doi.org/10.1108/JFC-06-2019-0081

Omarini, A., (2018). Banks, and fintechs: How to develop a digital open banking approach for the bank’s future. International Business Research, 11(9), 23-36, https://doi.org/10.5539/ibr.v11n9p23

Otoritas Jasa Keuangan. (2023). Laporan perlindungankonsumen sektor jasa keuangan 2023. Otoritas Jasa Keuangan, https://www.ojk.go.id/id/kanal/edukasi-dan-perlindungan-konsumen/Pages/Laporan-Perlindungan-Konsumen.aspx

Otoritas Jasa Keuangan. (2022). Statistik pengaduan konsumen sektor jasa keuangan. Otoritas Jasa Keuangan. https://www.ojk.go.id/id/kanal/edukasi-dan-perlindungan-konsumen/data-dan-statistik/Pages/Statistik-Pengaduan-Konsumen.aspx

Pahnila, S., Siponen, M., & Mahmood, A. (2017). Employee’s behavior towards IS security policy compliance. Information & Management, 54(1), 1-13, https://doi.org/10.1016/j.im.2016.08.004

Posey, C., Bennett, R.J., Roberts, T.L., & Lowry, P.B. (2018). When computer monitoring backfires: Invasion of privacy and organizational injustice as precursors to computer abuse. Information System Research, 29(2), 309-326, https://doi.org/10.1287/isre.2017.0739

Said, J., Alam, M.M., & Karim, Z.A. (2018). Integrating religiosity into fraud triangle theory: Empirical findings from Malaysia. Journal of Financial Crime, 25(2), 436-450, https://doi.org/10.1108/JFC-02-2017-0016

Seetharaman, A., Senthilvelmurugan, M., & Raj, J.R. (2017). Cybersecurity: Issues and challenges. Journal of Cyber Security Technology, 1(2), 1-10, https://doi.org/10.1080/23742917.2017.1288491

Venkatesh, V., Brown, S.A., & Bala, H. (2013). Bridging the qualitative-quantitative divide: Guidelines for conducting mixed methods research in information systems. MIS Quartertly, 37(1), 21-54, https://doi.org/10.25300/MISQ/2013/37.1.02

Vousinas, G.L. (2019). Advancing theory of fraud: The SCORE model. Journal of Financial Crime, 26(1), 372-381, https://doi.org/10.1108/JFC-12-2017-0128

Yu, S., Niu, X., & Chen, Y. (2020). Understanding cybercrime prevention behavior. Computers & Security, 92, 101751, https://doi.org/10.1016/j.cose.2020.101751

Zainal Abidin, A., Hashim, H.A., & Ariff, A.M. (2017). Ethical commitments and financial performance: Evidence from Malaysian public listed companies. Journal of Financial Crime, 24(2), 206-219, https://doi.org/10.1108/JFC-06-2016-0036

Zakira, N.B., Haron, R., & Zainol, M.S. (2021). Fraud prevention and internal control in digital settings. Journal of Financial Crime, 28(2), 533-549, https://doi.org/10.1108/JFC-07-2020-0131




DOI: https://doi.org/10.24167/jmbe.v8i1.15491

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