“Fraud does not just happen”: Red flags are waved, institutions turn a blind eye. Until it becomes a scandal.

“Fraud does not just happen”: Red flags wave, institutions turn a blind eye. It is a black hole that everyone knows, everyone sees, but no one recognizes it, until it becomes a scandal. Then everyone says, “How did this happen so suddenly, we never knew about it?”
Hasan Alsancak

There are some cases; when it makes the headlines, everyone says the same thing:
“It just happened, no one expected it.”

In reality, this is not true.
It develops slowly and quietly over months, sometimes years, raising red flags in the form of small but persistent deviations in behavior, numbers, processes. Research shows that if these red flags were seen and taken seriously, a significant proportion of cases could have been detected much earlier and the damage dramatically reduced (Stamler et al., 2014; Grabosky & Duffield, 2001; Sandhu, 2020; Moshi et al., 2025).

The problem is that institutions often choose to “ignore” these signals.

Fraud first becomes an “anomaly”, then a scandal

Studies in the field of fraud emphasize that the most basic red flag is the anomaly:
Deviation from expected behavior, performance or financial patterns (Grabosky & Duffield, 2001; Elsayed, 2017; Munteanu et al., 2024).

For example:

• Unexplained profitability increases disconnected from the industry average (Caesaria et al., 2025; Putri & Alam, 2025; Elsayed, 2017)- Sales and profit figures out of sync with cash flow (Caesaria et al., 2025; Tannaka et al., 2025)- Breaking down segregation of duties, concentrated authority in one person (Utami et al., 2020; Putri & Alam, 2025; Elsayed, 2017; Munteanu et al, 2024)- Sudden change in employee behavior: patterns such as overtime, isolation, job dissatisfaction, increase in standard of living out of line with income (Padgett, 2015; Sandhu, 2020; Moshi et al, 2025)Studies focusing on financial statement manipulation show that early detection of red flags significantly reduces the risk of manipulation and improves audit quality (Caesaria et al., 2025; Elsayed, 2017; Munteanu et al., 2024; Tannaka et al., 2025). Likewise, field studies on behavioral red flags reveal that 3-4 typical warning signs are observable months in advance in most people who commit fraud (Sandhu, 2020; Moshi et al., 2025).

In other words, fraud is not a momentary “event” but a process that is not wanted to be seen.

Why are so many red flags ignored?

Research shows that while red flags are technically detectable, organizations struggle to turn them into a systematic early warning mechanism (Utami et al., 2020; Stamler et al., 2014; Koornhof & Plessis, 2000; Moshi et al., 2025). There are several critical reasons for this:

1. Reactive culture, instead of proactive Many organizations deal with fraud only after a crisis. However, even in highly regulated industries such as banking, strong internal controls and a healthy organizational culture have been proven to act as an early warning for fraud (Utami et al., 2020).
2. Low red flag awareness Both internal and external auditors recognize the importance of red flags, but structured checklists and systematic use of these signals are often lacking (Gullkvist & Jokipii, 2013; Koornhof & Plessis, 2000). Studies show that increased red flag awareness and professional skepticism significantly improve fraud detection performance (Siringorongo et al., 2025; Ramadhany et al., 2025).
3. Underestimating behavioral signals Interviews in the fieldshow that employees who engage in misconduct often exhibit recurring behavioral red flags – excessive ambition, long working hours, social distancing, job dissatisfaction, a standard of living mismatched with income, etc. (Sandhu, 2020; Moshi et al., 2025). Yet these symptoms are normalized in many organizations as “personal issues”, “hard work” or “character issues”.
4. Data but no system! Studiesin the bankingand finance sector emphasize that institutions are in fact collecting data on early warning signals, but lack integrated systems that transform these signals into real-time risk scoring (Roy & P., 2024; Shrimali, 2025; Trivedi et al., 2024).

Red Flags – Early warning signals: The only realistic way to cut the damage before it grows

Current literature makes it clear that a shift from a reactive to a proactive, early warning-oriented approach to fraud management is imperative (Roy & P., 2024; Shrimali, 2025; Stamler et al., 2014; Tannaka et al., 2025).

Three layers are critical for this:

1. Structural controls and internal control environment
   • Strong internal control and well-designed organizational culture serve as early warning mechanisms for fraud (Utami et al., 2020; Munteanu et al., 2024; Kurniawati, 2021).
   • Internal control weaknesses and lack of control are the main triggers in a significant proportion of fraud cases (Utami et al., 2020; Caesaria et al., 2025; Munteanu et al., 2024; Kurniawati, 2021).
2. Red flag systematics
   • Red flags can be classified in a wide range of categories, from financial anomalies to behavioral signs (Caesaria et al., 2025; Grabosky & Duffield, 2001; Padgett, 2015; Elsayed, 2017).
   • Both theoretical and empirical studies show that red flag lists (ISA 240, SAS 99, etc.) provide a meaningful early warning function to auditors and practitioners (Caesaria et al., 2025; Elsayed, 2017; Munteanu et al., 2024; Tannaka et al., 2025; , 2025).
   • Studies on cooperatives, banks and other institutions show that the impact of behavioral and operational red flags on fraud detection is statistically significant and strong (Utami et al., 2020; Moshi et al., 2025).
3. Technology-enabled early warning mechanisms
   • Early warning systems powered by machine learning, artificial intelligence and big data analytics enable real-time risk detection and prioritization, especially in banking and credit fraud (Roy & P., 2024; Shrimali, 2025; Trivedi et al., 2024).
   • Early warning signals used in lending have been shown to be critical in predicting high fraud risk, especially in areas such as diversion of funds, transaction concentrations, and collateral issues (Trivedi et al., 2024).

The organization that sees red flags and fails to act pays the bill in multiples

Both case studies and empirical research point to the same reality:
If red flags are not recognized and action is not taken in time, both financial loss and reputational damage increase exponentially (Shrimali, 2025; Stamler et al., 2014; Munteanu et al., 2024; Kurniawati, 2021).

Some findings:

• Early interpretation of red flags significantly reduces the monetary amount and duration of fraud (Stamler et al., 2014; Munteanu et al., 2024; Kurniawati, 2021).
• Organizations that are responsive to behavioral and operational red flags detect fraud earlier, reducing overall losses (Sandhu, 2020; Moshi et al., 2025).
• The detection performance of internal audit teams trained in red flag awareness and professional skepticism significantly increases (Siringorongo et al., 2025; Ramadhany et al., 2025).

The cost of delay is not just on the balance sheet:

• Regulatory sanctions,
• Loss of investor confidence,
• It has long-lasting and irreversible consequences, such as the disengagement of talented employees (Shrimali, 2025; Stamler et al., 2014; Tannaka et al., 2025; Koornhof & Plessis, 2000).

A clear message for leaders: Make “no misconduct happens overnight” a corporate principle

Research shows that there are still a majority of organizations that recognize the importance of red flags but do not link them to a structural system (Gullkvist & Jokipii, 2013; Koornhof & Plessis, 2000).

Actionable framework for leaders:

• Position red flags not as “exaggerated skepticism” but as a corporate immune system.
• Establish clear lists, thresholds and action protocols for financial, operational and behavioral red flags (Caesaria et al., 2025; Padgett, 2015; Elsayed, 2017; Munteanu et al., 2024).
• Support internal audit, risk and compliance teams with regular training on red flag awareness, professional skepticism and data-driven early warning systems (Siringorongo et al., 2025; Ramadhany et al., 2025; Moshi et al., 2025).
• Use technology for immediate early warning, not for “forensic analysis afterwards” (Roy & P., 2024; Shrimali, 2025; Trivedi et al., 2024).

Final word: Silent signals are never really silent

Red flags never “appear out of thin air”;

• Numbers whisper first,
• Processes are singular,
• Behavior changes,
• Then one day it becomes a headline.

“No abuse comes out of nowhere.”

The question is: Is your organization ready to hear those slow and quiet signals? Or does it choose not to?

The Role of Early Warning and Red Flags (Summary)

Figure 1: The main roles red flags play in early detection

References

Roy, N., & P., S. (2024). Proactive cyber fraud response: a comprehensive framework from detection to mitigation in banks. Digital Policy, Regulation and Governance. https://doi.org/10.1108/dprg-02-2024-0029

Utami, W., Nugroho, L., Mappanyuki, R., & Yelvionita, V. (2020). Early Warning Fraud Determinants in Banking Industries. Asian Economic and Financial Review. https://doi.org/10.18488/journal.aefr.2020.106.604.627

Caesaria, S., Murti, G., & Mayasha, E. (2025). RED FLAGS DALAM MENDETEKSI KECURANGAN: ANALISIS FAKTOR PEMICU FRAUD PADA LAPORAN KEUANGAN. Jurnal Riset Akuntansi Politala. https://doi.org/10.34128/jra.v8i1.448

Shrimali, A. (2025). Banking Frauds and Their Impact: Harnessing Technology for Early Detection. International Journal of Advanced Research in Science, Communication and Technology. https://doi.org/10.48175/ijarsct-23159

Siringorongo, M., Hasugian, C., Simanjuntak, S., Lumbangaol, M., & Simanjuntak, M. (2025). Auditor Capability on the Effectiveness of Red Flags in Detecting Fraud. Jurnal Ilmiah Manajemen Kesatuan. https://doi.org/10.37641/jimkes.v13i3.3301

Stamler, R., Marschdorf, H., & Possamai, M. (2014). Fraud Prevention and Detection: Warning Signs and the Red Flag System. **. https://doi.org/10.1201/b16665

Putri, M., & Alam, I. (2025). PENGARUH KUALITAS PELAYANAN KEPADA KEUNGGULAN BERSAING MELALUI KEPUASAN PELANGGAN SEBAGAI VARIABEL INTERVENING DI JUICECOVERY LAMPUNG. Jurnal Riset Akuntansi Politala. https://doi.org/10.34128/jra.v8i1.459

Grabosky, P., & Duffield, G. (2001). Red Flags of Fraud. Trends and issues in crime and criminal justice, 1. https://doi.org/10.1002/9781118386064.ch3

Trivedi, S., Krishnakumar, D., & Bajaj, R. (2024). Loan Frauds in the Indian Banking Industry: A New Approach to Fraud Prevention Using Natural Language Processing (NLP). Asia-Pacific Financial Markets, 32, 773 – 799. https://doi.org/10.1007/s10690-024-09470-x

Gullkvist, B., & Jokipii, A. (2013). Perceived importance of red flags across fraud types. Critical Perspectives on Accounting, 24, 44-61. https://doi.org/10.1016/j.cpa.2012.01.004

Padgett, S. (2015). Behavioral Warning Signs or Red Flags. **, 71-84. https://doi.org/10.1002/9781118929773.ch9

Elsayed, A. (2017). Indicators of the Financial Statement Fraud (Red Flags). International Corporate Finance eJournal. https://doi.org/10.2139/ssrn.3074187

Ramadhany, A., Erlina*, E., Sadalia, I., & Fachrudin, K. (2025). Enhancing Fraud Detection Performance: The Interplay of Red Flag Awareness, Self-Efficacy, and Professional Skepticism. Journal of Risk and Financial Management. https://doi.org/10.3390/jrfm18060301

Munteanu, V., Zuca, M., Horaicu, A., Florea, L., Poenaru, C., & Anghel, G. (2024). Auditing the Risk of Financial Fraud Using the Red Flags Technique. Applied Sciences. https://doi.org/10.3390/app14020757

Tannaka, J., Stevanie, E., & Olivia, O. (2025). Penerapan Red Flags Analysis dalam Mendeteksi Potensi Financial Statement Fraud di Pasar Modal Indonesia. Maslahah : Jurnal Manajemen dan Ekonomi Syariah. https://doi.org/10.59059/maslahah.v3i3.2369

Sandhu, N. (2020). Behavioral Red Flags of Fraud: An Ex Post Assessment of Types and Frequencies. Global Business Review, 21, 507 – 525. https://doi.org/10.1177/0972150919850410

Kurniawati, A. (2021). Red Flags to Detect Fraudulent Financial Reporting in Indonesian Banking Sector. Proceedings of the 2nd International Conference on Business and Management of Technology (ICONBMT 2020). https://doi.org/10.2991/aebmr.k.210510.049

(2025). Fraud Examination in Government-Aided Institutions:Empirical Analysis of Red Flags, Detection, and Prevention. European Economic Letters. https://doi.org/10.52783/eel.v15i3.3732

Koornhof, C., & Plessis, D. (2000). Red flagging as an indicator of financial statement fraud: The perspective of investors and lenders. Meditari Accountancy Research, 8, 69-93. https://doi.org/10.1108/10222529200000005

Moshi, J., Machimu, G., & Mataba, L. (2025). Fraud Detection in Savings and Credit Cooperative Societies in Tanzania: Do Red Flags Matter?. International Journal of Community and Cooperative Studies. https://doi.org/10.37745/ijccs.2014/vol13n13245