How Can Companies Test Whether Their Fraud Controls Actually Work?

Having fraud controls in place is only the first step. Businesses also need to know whether those controls work in practice. This article explores how organisations can evaluate their fraud detection, monitoring and response capabilities to identify weaknesses and strengthen their resilience against evolving threats.

Fraud prevention systems can appear comprehensive on paper, but their effectiveness is not always easy to establish. An organisation might have sophisticated monitoring technology, documented approval procedures and a detailed risk assessment framework, yet still struggle to identify suspicious activity or respond quickly when a threat emerges.

As criminals increasingly use artificial intelligence (AI) to make fraud more convincing and difficult to detect, businesses need greater assurance that their existing safeguards are performing as intended.

This means moving beyond checking whether controls are in place and examining the evidence of how well they operate. Regular evaluation helps organisations understand where their fraud defences are effective, where weaknesses remain and what needs to improve.

Moving from Control Design to Control Effectiveness

There is an important difference between having a well-designed fraud control and knowing that it works.

A transaction monitoring system may be configured to identify unusual activity, but that does not necessarily mean it will recognise emerging fraud patterns. Similarly, an onboarding process may require identity verification, yet still fail to identify inconsistencies across multiple applications or relationships.

Evaluating control effectiveness involves examining how systems perform under normal operating conditions, whether they identify genuine risks and how reliably those risks are managed. It also means considering whether controls are working together rather than operating independently across different departments or business functions.

Organisations should establish clear criteria for assessing performance and use the findings to inform improvements. This provides a more objective basis for understanding fraud exposure and determining whether existing investment in prevention and detection is delivering the intended protection.

Using Penetration Testing and Red Teaming to Evaluate Controls

Penetration testing provides a practical way to assess whether an organisation’s systems and access controls can withstand real-world attacks. By simulating the techniques used by criminals, external penetration testing can expose vulnerabilities in websites, applications, customer portals and other externally accessible systems that could provide opportunities for fraud.

While penetration testing typically focuses on identifying exploitable technical weaknesses, Red Teaming takes a broader approach. It simulates a determined attacker pursuing a defined objective, potentially combining cyber attacks, social engineering and other techniques to assess how effectively an organisation’s people, processes and technology work together. This can reveal weaknesses that might not become apparent when individual controls are tested in isolation.

Both approaches provide valuable evidence of control effectiveness. However, identifying vulnerabilities is only the beginning. Organisations need to evaluate the findings, prioritise remedial action according to risk and verify that weaknesses have been addressed through subsequent testing. This helps establish whether improvements have genuinely strengthened the organisation’s defences.

Prevention testing should test deterrence, secure product design, transaction friction, employee access controls, and fraud-resistant customer journeys. Consider prevention rate, attempted versus realised loss, false-negative rate, customer harm, recurrence, recovery rate, and time to contain.

End-to-end scenario testing should allow effective tracing of realistic fraud scenarios across prevention, detection, investigation, customer support, recovery, and remediation.

An effective testing framework should support a risk-based test plan covering scope, frequency, independence, sampling, evidence standards, or pass/fail criteria.

Assessing Fraud Detection and Monitoring Performance

Fraud detection technology plays a central role in identifying suspicious activity, but its effectiveness depends on the quality of the information it processes and the relevance of the alerts it produces.

AI-enabled monitoring systems can analyse external-party interactions to identify unusual behaviour, including repeated application attempts, automated interactions, unexpected transaction patterns or activity that differs from an established profile. These capabilities can be particularly valuable where organisations handle large volumes of applications or transactions across multiple channels.

However, generating alerts is not the same as detecting fraud effectively. Businesses need to establish whether their monitoring systems are identifying meaningful threats without overwhelming teams with unnecessary investigations. Excessive false positives can consume resources and create alert fatigue, while overly restrictive detection rules may allow suspicious activity to go unnoticed.

Performance reviews should therefore consider the accuracy and relevance of alerts, the speed with which they are investigated and whether confirmed fraud cases reveal patterns that existing systems failed to detect. These findings can help organisations refine monitoring rules, improve automated triage and prioritise activity according to the level of risk involved.

Where AI models support detection, their performance should be reviewed regularly to establish whether they remain effective as fraud techniques and transaction behaviours change.

Prevention metrics derived from monitoring fraud attempts successfully blocked, declined fraudulent applications and negative listing matches should be implemented to promote sustained investment in preventative measures.  

Reviewing Risk Scoring and Due Diligence Decisions

Risk scoring provides a structured way to assess the fraud exposure associated with different customers, suppliers, applicants and other third parties. However, its value depends on whether the scores accurately reflect risk and lead to appropriate decisions.

A company-wide risk assessment matrix should establish consistent criteria for evaluating different types of relationships and activities. These assessments can then inform the level of due diligence applied during onboarding, the intensity of ongoing monitoring and whether additional management approval is required.

To evaluate effectiveness, organisations should examine whether risk classifications correspond with the outcomes of subsequent investigations and monitoring activity. If relationships initially classified as low risk repeatedly generate serious fraud concerns, this may indicate weaknesses in the assessment criteria or the information used to calculate scores.

Businesses should also review whether higher-risk applications receive appropriate scrutiny and whether approval decisions remain consistent with established risk appetite thresholds. Where automated scoring models are used, their accuracy should be regularly validated, with findings incorporated into future model development.

The objective is to ensure that risk scoring remains a reliable decision-making tool rather than simply an administrative step in the onboarding process.

Third-party exposure could be detailed further with outsourced services, platforms, data providers with the complexities of shared accountability.

Using Data Analysis to Identify Hidden Fraud Patterns

Individual transactions or applications may appear legitimate when viewed in isolation. Analysing information across multiple interactions can reveal patterns that suggest a wider fraud threat.

This makes the quality and completeness of the organisation’s data particularly important. Information relating to unsuccessful applications, abandoned onboarding processes, terminated accounts and previously confirmed fraud cases can provide valuable intelligence that might otherwise be overlooked.

For example, analysis of historical fraud records and negative listings may reveal repeated applications associated with particular devices, identities or behavioural characteristics. It may also help identify patterns associated with mule accounts, unusual transaction velocity or activity across connected parties that warrants further investigation.

Organisations should assess whether their data collection arrangements are sufficiently comprehensive to support this analysis and whether relevant information can be compared across different systems. Where appropriate, cross-referencing applicant details against trusted external sources can help identify inconsistencies and provide additional assurance, particularly in complex supply chains or higher-risk relationships.

The findings should be used to improve fraud detection capabilities rather than remaining isolated within reporting systems. By incorporating validated insights into monitoring rules, risk assessments and AI model development, businesses can strengthen their ability to recognise emerging threats. Any collection and use of personal data must also comply with applicable data protection requirements.

Data and AI model governance could be developed by addressing concepts such as data lineage, bias, explainability, drift thresholds, privacy, validation independence, model maintenance and change control. 

Measuring the Effectiveness of Fraud Reporting and Response

Identifying suspicious activity is only one measure of fraud control effectiveness. Organisations also need to establish whether concerns are reported, investigated and resolved efficiently.

Suspicious activity reporting systems should make it straightforward for employees to record relevant warning signs, provide supporting evidence and explain the reasoning behind their concerns. The information captured needs to be sufficiently detailed to support investigation while remaining accessible only to those with an appropriate business need.

Consumer vulnerability affects fraud exposure, customer interactions, authentication, intervention design, and fair treatment.

Regular reviews of reporting activity can reveal whether concerns are being escalated consistently, whether investigations are progressing promptly and whether recurring issues are being addressed. Where reporting volumes are unexpectedly low, organisations should consider whether this reflects genuinely limited suspicious activity or barriers that discourage employees from raising concerns.

Response performance is equally important. Desktop exercises provide a controlled environment in which organisations can evaluate how effectively their fraud response arrangements operate when faced with realistic threats, including AI-enabled fraud. They can expose delays in decision-making, uncertainty around responsibilities and weaknesses in communication between teams.

As explored in our previous article, What Fraud Scenarios Should Every Business Test?, realistic exercises are an important part of challenging an organisation’s fraud defences. The findings should be used to measure response effectiveness, identify areas for improvement and establish whether subsequent changes have successfully addressed the weaknesses identified.

People testing can be a challenge: General practices encourage individual assessment rather than testing the effectiveness of training, implementation of processes, staffing, incentives and work supervision collectively.  

Turning Findings into Continuous Improvement

Fraud control testing delivers the greatest value when the results lead to meaningful changes in how an organisation manages risk.

Rather than treating assessments as isolated activities, businesses should bring together findings from penetration testing, monitoring systems, suspicious activity reports, investigations and other assurance exercises. Reviewing this information collectively can reveal weaknesses that might not be apparent when individual controls are assessed separately.

Performance measures can help organisations track whether improvements are having the intended effect. For example, a reduction in unnecessary alerts may indicate more accurate detection rules, while faster investigation times may demonstrate that revised escalation procedures are working. Where weaknesses persist, further analysis may be needed to establish whether the underlying issue relates to technology, process design or the way controls are being applied.

People also remain an important consideration. Staff performance reviews and the findings from practical exercises can help establish whether employees are using fraud risk tools correctly and applying procedures consistently. This provides a more useful measure of training effectiveness than completion rates alone and allows further development to be targeted where it is most needed.

Effective improvement depends on collaboration between fraud, cyber security, compliance, operational and management teams. By sharing findings, agreeing ownership of corrective actions and reviewing progress, organisations can ensure that lessons learned translate into lasting improvements rather than remaining as recommendations in assessment reports.

Independent assurance should challenge second-line, internal audit, external validation, or testing team independence.

Good governance should provide reporting channels on risk appetite tolerance breaches, overdue remediation and exceptions

How AJC Can Help

At AJC, we help organisations understand how effectively their fraud controls operate and identify opportunities to strengthen their existing defences.

Our Fraud Risk Consultancy team supports businesses with fraud risk assessments, governance frameworks, risk appetite statements, policies, procedures and remediation planning. We work with organisations to evaluate their existing control environment, identify vulnerabilities and develop practical recommendations aligned with their risk exposure and operational needs.

Through our Penetration Testing Services and Red Teaming capabilities, we also help businesses identify exploitable weaknesses and assess how effectively their systems, people and processes withstand realistic attacks. Our approach focuses on providing clear findings, prioritised recommendations and practical support to address the vulnerabilities identified.

We also support organisations through fraud awareness training, phishing training, social engineering exercises and scenario-based desktop exercises, including those involving AI-enabled fraud. Together, these services help businesses evaluate their resilience, strengthen fraud prevention and improve their ability to detect and respond to evolving threats.

Our approach focuses on providing clear, proportionate and practical support that helps organisations strengthen fraud prevention, improve accountability and build long-term resilience.

Final Thoughts

The effectiveness of fraud controls cannot be judged solely by the policies, procedures or technology an organisation has in place. What matters is whether those controls consistently identify genuine threats, support appropriate decisions and enable an effective response.

Regular evaluation provides the evidence businesses need to understand where their fraud defences are performing well and where further attention is required. By examining detection accuracy, risk scoring, data quality, reporting performance and the outcomes of control testing, organisations can make more informed decisions about how to strengthen their protection.

As fraud methods continue to evolve, businesses need to ensure that their controls evolve with them. The goal is not simply to demonstrate that safeguards exist, but to establish that they remain effective against the threats the organisation faces.

If you would like support reviewing or testing the effectiveness of your fraud controls, contact AJC on 020 7101 4861 or email info@ajollyconsulting.co.uk to discuss your requirements.