Beyond the Numbers: Using Behavioural Indicators to Detect Fraud Early
Fraud rarely starts as a number. It starts as behaviour: repeated “exceptions”, manufactured urgency, discouraged challenge, and management overrides that become routine.
In our latest article, Beyond the Numbers: Using Behavioural Indicators to Detect Fraud Early, we explore how non-financial data, such as employee behaviour patterns, override footprints, and cultural red flags, can surface fraud risk months before traditional audits would typically detect it.
If your organisation is still relying on periodic reviews and transaction sampling alone, you may be arriving late to the problem. A behavioural early-warning lens helps you investigate faster, protect good employees, and remediate root causes.
Read the full article and let us know which behavioural signals you see most often in practice.
Beyond the Numbers: Using Behavioural Indicators to Detect Fraud Early
Authored by Duja Consulting
Executive overview
Most fraud does not begin with a spreadsheet anomaly. It begins with a person testing boundaries: bypassing a process “just this once”, discouraging questions, normalising exceptions, and recruiting others to comply or stay silent. By the time the financial impact becomes visible, the behaviour has often been entrenched for months or years. This is why modern forensic capability cannot rely on financial signals alone.
Behavioural indicators and other non-financial data sources, such as employee conduct, management override patterns, access and workflow traces, speak-up activity, and cultural red flags, provide earlier warning signals than traditional audits typically detect. These indicators do not replace financial controls; they strengthen them by revealing intent, opportunity, pressure, and rationalisation in real time.
This article sets out practical behavioural signals to monitor, how to distinguish legitimate urgency from manipulation, how to evidence management override, and how to translate “soft” cultural risks into defensible forensic leads. It also offers an implementation playbook: data sources, governance, investigation protocols, and safeguards to ensure ethical use. The goal is not to surveil employees. The goal is to protect the organisation by detecting fraud risk earlier, investigating smarter, and preventing repeat incidents that conventional approaches often miss.
Introduction
Traditional audits are designed to provide assurance over financial statements and control environments, not to catch every instance of misconduct early. They sample transactions, verify documentation, and test controls at specific points in time. Fraudsters exploit the gaps: they operate between audit cycles, keep transaction values below review thresholds, and use legitimate processes to conceal illegitimate intent.
Behavioural indicators close this gap by revealing patterns that precede financial loss. These indicators show how work is actually done: who overrides approvals, who avoids peer review, who creates urgency without evidence, who isolates key processes, who punishes challenge, and who repeatedly “fixes” exceptions that they themselves create.
Non-financial data is now abundant. Access logs show who entered systems and when. Workflow tools show approvals, reversals, and rework. Communications metadata can identify unusual spikes in after-hours coordination. Human resources records show staff turnover, grievances, and repeated allegations. Whistleblowing channels reveal themes long before they reach the balance sheet. When used responsibly, this data becomes a powerful early-warning lens for forensic teams and risk leaders.
Below are practical ways to incorporate behavioural signals into fraud detection and investigation, without turning the workplace into a culture of suspicion.
2. Employee behavioural indicators that often precede fraud
Fraud risk is not “a type of person”, but certain behaviours are repeatedly associated with concealment, manipulation, and control. Investigators should be careful not to label, but to treat these as signals that warrant a closer look when they cluster together.
Common behavioural indicators include: refusal to take leave, reluctance to share passwords or process knowledge, and defensiveness when questioned about routine matters. Another frequent sign is over-control: insisting that all supplier or customer communication flows through one person, or blocking colleagues from accessing “their” files, “their” inbox, or “their” vendor relationships.
Watch for patterns of manufactured urgency: repeated “must pay today” requests without supporting documentation, frequent last-minute changes, and exaggerated consequences if approvals are not immediate. Fraudsters create time pressure to bypass scrutiny. Also note sudden lifestyle shifts that cannot be explained by remuneration alone, but treat these carefully and ethically; lifestyle is a weak indicator unless supported by process evidence.
Finally, pay attention to boundary-testing: small policy breaches that are laughed off, repeated “exceptions”, and a culture of casual non-compliance. Fraud often escalates from tolerated minor misconduct.
3. Management override as a behavioural pattern, not a single event
Management override is one of the most damaging and under-evidenced fraud enablers. It is rarely a dramatic instruction to “ignore controls”. It is more often a pattern: approvals granted without documentation, repeated retrospective authorisations, frequent rule changes “just for this case”, and the systematic weakening of segregation of duties.
A robust approach treats override as a measurable behavioural footprint. Examples include: approvals outside policy thresholds, override reasons that are vague or copied and pasted, high rates of after-hours approvals, and a recurring use of emergency workflows. Another signal is when a manager routinely directs staff to bypass normal channels, such as paying from an alternative cost centre, using a different vendor record, or “processing it as a journal” rather than through standard procurement controls.
The forensic value lies in trend analysis. One override may be legitimate. A repeated pattern by the same approver, for the same supplier, with the same justifications, indicates elevated risk.
Organisations should preserve and analyse override logs, approval trails, and workflow histories because these become high-quality evidence when financial losses are later uncovered.
4. Cultural red flags that traditional audits often underestimate
Culture is often treated as intangible, but it has observable markers that correlate strongly with misconduct risk. A culture that discourages challenge creates the perfect environment for fraud to persist.
Red flags include fear-based leadership, retaliatory behaviour towards whistleblowers, and a tendency to label questioning as disloyalty. Another indicator is “performance at all costs”: unrealistic targets, public shaming for misses, and a tolerance for cutting corners to “get results”. When people believe outcomes matter more than methods, fraud rationalisation becomes easier.
A further cultural signal is inconsistent discipline: junior employees are punished for minor breaches, while senior employees face no consequence for major breaches. This undermines ethical norms and increases the likelihood that employees will either participate in misconduct or remain silent about it.
Forensic teams should include cultural evidence in scoping: staff interviews, grievance themes, repeated allegations, turnover spikes in specific teams, and patterns in exit interviews. These are not proof of fraud, but they often show where to look and why controls failed.
5. The “triangle” becomes practical when you measure behaviour
Fraud risk is often explained through three drivers: pressure, opportunity, and rationalisation. Behavioural indicators make these drivers practical and observable.
Pressure shows up as repeated crisis language, secretive financial stress discussions, or sudden changes in personal circumstances that coincide with process access. More importantly, pressure can also be organisational: unrealistic deadlines, chronic understaffing, and targets that are incompatible with compliance.
Opportunity is visible in access patterns: one person controlling multiple steps, frequent elevated access approvals, manual workarounds, and weak segregation of duties. Opportunity also shows up in process complexity: many handoffs, unclear ownership, and excessive exceptions.
Rationalisation appears in language and norms: “everyone does it”, “the policy is stupid”, “this is how we survive here”, or “head office does not understand reality”. When such narratives are common, the organisation should treat them as a risk signal and strengthen both controls and culture interventions.
6. Non-financial data sources that add immediate forensic value
Many organisations already hold the data they need, but it sits in silos. Practical sources include: system access logs, workflow approvals, ticketing systems, procurement and vendor onboarding trails, payroll change histories, inventory adjustment records, and helpdesk access requests. These provide time-stamped evidence that is difficult to dispute.
Human resources data adds context: disciplinary cases, repeated grievances, conflict patterns, and turnover clusters. Speak-up channel data provides early themes and network clues, especially when multiple reports refer to the same department, vendor, or manager behaviour.
Physical security logs, where applicable, can support timelines: after-hours access, unusual entry patterns, and access to restricted areas. Travel and expense claims provide behavioural signals through repeated exceptions, high rates of manual receipts, or patterns that align with specific vendors.
The key is not to collect everything. The key is to define a small set of “high signal” indicators per risk hotspot and then build repeatable analytics that highlight change over time.
7. Behavioural analytics that detect schemes earlier than sampling
Traditional audit sampling can miss low-value, high-frequency fraud. Behavioural analytics is well-suited to detect it. Examples include: repeated transaction splitting just below approval thresholds, consistent use of the same approver for “urgent” payments, and frequent reversals followed by re-approvals.
Another powerful technique is peer comparison. If one team processes far more manual overrides than comparable teams, this may indicate either a training issue or deliberate manipulation. Similarly, if one manager has a materially higher exception rate, investigate the driver.
Sequence analysis is also useful: a vendor is created, bank details are amended shortly thereafter, and payments follow quickly with minimal supporting documentation. Even when the amounts appear normal, the behavioural sequence can indicate a potential kickback or vendor impersonation scheme.
Network patterns matter too. If a small set of employees repeatedly interact with the same set of vendors and approve each other’s exceptions, this clustering can be a lead. These approaches do not prove guilt; they prioritise investigative focus with speed and defensibility.
8. Interviews: how to evidence behavioural red flags without bias
Interviews are where behavioural indicators become evidential. However, interviewers must avoid assumptions and confirmation bias. The objective is to test hypotheses, not to “get a confession”.
Use structured interview planning: define the process narrative, list points of discretion, identify what “good” looks like, and then test deviations through facts. Ask open questions first, then progressively narrow. For example: “Walk me through how urgent payments are handled” followed by “What documentation is required” followed by “Why was documentation missing in these five cases.”
Observe behavioural cues carefully but interpret them conservatively. Nervousness may reflect fear, not guilt. The stronger evidence is inconsistency: changing explanations, inability to describe routine steps, or deflection towards blaming others without specifics.
Corroborate interview statements with system evidence. When a person claims “the system made me do it”, test whether the system log supports it. When someone claims “I had no access”, test access records. The combination of behavioural observation and objective logs is where investigations become robust.
9. Turning “soft” signals into defensible evidence
One reason organisations underuse behavioural indicators is fear that they are too subjective. The solution is to operationalise them. Convert cultural and behavioural red flags into measurable proxies and evidential artefacts.
For example, “management override culture” becomes: override frequency, override timing, override justification quality, and override concentration by individual. “Fear culture” becomes: grievance frequency, exit interview themes, turnover spikes, and retaliation allegations. “Process ownership concentration” becomes: segregation of duties breaches, access rights clustering, and single-person dependency indicators such as refusal to delegate or take leave.
Where possible, anchor your behavioural case in documentation: workflow trails, policy exceptions, meeting minutes that record control waivers, approval emails, or ticketing system evidence of access changes.
When behavioural indicators are treated as structured evidence, they hold up far better in disciplinary processes, regulatory engagement, and potential litigation.
10. Designing early-warning dashboards without creating a surveillance culture
A behavioural lens must be implemented with care. Employees should not feel monitored for personal reasons; the organisation should focus on process integrity and risk prevention.
Good practice includes transparency about what is monitored and why, clear governance, and tight access controls around sensitive data. Focus indicators on high-risk processes and objective artefacts: approvals, overrides, access rights, and exception volumes. Avoid intrusive monitoring unless there is a specific investigation with appropriate authorisation.
Set thresholds and escalation rules that recognise operational realities. For example, month-end periods may legitimately increase after-hours approvals. Adjust baselines accordingly. Also ensure leaders are held to the same standards; behavioural dashboards lose credibility if they are used only against junior staff.
Finally, pair early-warning indicators with prevention actions: process redesign, training, segregation of duties improvements, and leadership accountability. Detection without remediation simply documents failure.
11. Prevention actions that directly reduce behavioural fraud risk
Early detection should trigger targeted prevention. If override patterns are high, strengthen independent review and require documented rationale that can be tested. If one person controls too much, redesign roles and enforce mandatory leave and rotation in sensitive functions.
Where urgency is routinely used to bypass controls, introduce “fast lanes” that are still controlled: pre-approved vendor lists, standard emergency templates, and dual approvals for urgent workflows. Remove the excuse that “controls slow us down” by designing controls that work at operational speed.
If cultural red flags are present, address leadership behaviour directly. Ethical culture is not a poster; it is a set of consequences. Reward challenge, protect whistleblowers, and discipline misconduct consistently across levels.
Invest in practical training that teaches managers how to spot manipulation tactics: manufactured urgency, narrative control, and subtle coercion. In many cases, managers approve questionable requests not because they are complicit, but because they are untrained and overwhelmed.
12. A practical implementation roadmap for organisations
A pragmatic roadmap begins with selecting three to five fraud hotspots and defining a behavioural indicator set for each. Build a minimal viable analytics capability before expanding.
Step four is investigative protocol: define how leads are triaged, who conducts preliminary fact finding, and how evidence is preserved. Step five is feedback: close the loop by learning from investigations and adjusting indicators and controls accordingly.
Step one is data mapping: identify where approval trails, override logs, access records, and exception workflows are stored. Step two is governance: define who owns the indicators, who can view them, and what triggers escalation. Step three is baselining: measure normal exception rates and seasonal patterns so you can detect meaningful change.
Most importantly, ensure executive sponsorship. Behavioural indicators often implicate leadership practices, not only employee conduct. Without executive support, early-warning systems become politically constrained and lose effectiveness. With support, they become a strategic asset that protects value and trust.
Conclusion
Fraud is frequently a behavioural phenomenon long before it becomes a financial one. If organisations wait for anomalies in the numbers, they often arrive late to the problem, facing larger losses, weaker evidence, and greater reputational damage. By incorporating behavioural indicators, management override patterns, and cultural red flags into forensic capability, organisations can detect risk earlier, investigate more intelligently, and remediate root causes rather than symptoms.
The most effective approach is balanced: rigorous in evidence, ethical in implementation, and practical in focus. Behavioural indicators should strengthen process integrity and protect good employees, not create an atmosphere of suspicion. When designed properly, they provide a defensible early-warning lens that traditional audits were never built to deliver.
Duja Consulting supports organisations in building behavioural fraud detection frameworks, strengthening investigation readiness, and conducting forensic investigations that go beyond the ledger to uncover what really happened, how it happened, and how to prevent repeat incidents. If you would like to discuss your risk hotspots and what an early-warning capability could look like in your environment, connect with Duja Consulting.
