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Neither control replaces the other. Continuous transaction monitoring is best at scanning complete payment populations and flagging suspicious activity quickly. Periodic independent audits are best at testing whether controls are well designed, examining evidence and governance, and finding risks that transaction rules miss. A public body gets the strongest protection by combining risk-based monitoring, scheduled independent audits and formal reviews that use results to change controls.
The practical answer: use a hybrid control system
Continuous transaction monitoring repeatedly analyzes transactions as they are created, approved or settled. Rules or statistical models can identify duplicate payments, unusual vendors, conflicts of interest, threshold breaches, abnormal timing and other known indicators. When data arrive quickly and an agency has people who can investigate alerts, monitoring can limit the time between a suspicious event and a response.
Periodic audits operate on a planned or targeted schedule. Auditors select evidence, test controls, review overrides and approvals, assess segregation of duties, examine third parties and challenge management assumptions. They can investigate qualitative and non-transactional risks that a transaction feed cannot represent, and they provide an assurance function that is more independent than an operational monitoring team.
The deciding factor is not whether a tool runs continuously. It is whether the agency can turn an alert or audit finding into a documented investigation, escalation, recovery or control change. A dashboard that produces large numbers of unreviewed alerts creates activity, not effective fraud control.
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How the two approaches work
Continuous transaction monitoring
A monitoring program ingests transaction and reference data, applies rules or models, creates alerts and routes those alerts to case owners. A mature workflow records the threshold that fired, the person responsible for triage, the escalation deadline, the evidence collected and the final disposition. It can test an entire population rather than a sample, which is particularly useful for high-volume or fast-moving payments.
- Typical signals: duplicate invoices or bank details, payments just below approval thresholds, unusual vendors, conflicts, rapid changes to supplier information and activity outside an expected pattern.
- Strength: speed and broad population coverage. An alert can arrive during or soon after a transaction, before additional payments accumulate.
- Operating burden: reliable data integration, rule and model maintenance, alert triage, investigators, case management and controls for false positives.
- Blind spot: a rule only detects what its data and logic represent. A novel scheme, a manipulated reference field or a control-design weakness may pass without an alert.
Periodic audits and targeted testing
An audit establishes scope, gathers evidence and performs procedures at scheduled intervals or in response to a risk. It can test whether a control is appropriately designed, whether staff actually follow it and whether exceptions are authorized. Surprise or targeted testing can increase perceived scrutiny, while independent fieldwork can examine controls operated by contractors or other public bodies.
- Typical work: walkthroughs, sampling, confirmation, reconciliation, review of access and approval rights, examination of overrides and root-cause analysis of exceptions.
- Strength: independence, judgment and the ability to assess governance, control design, qualitative evidence and non-transactional risks.
- Operating burden: planning, skilled auditors, evidence requests, interviews and time to complete and report fieldwork.
- Blind spot: scheduled work can identify a problem retrospectively, and sampling may not reveal a low-frequency event unless risk assessment directs the procedures appropriately.
Side-by-side comparison
| Dimension | Continuous transaction monitoring | Periodic audits |
|---|---|---|
| Speed | Can alert during or soon after a transaction. | Usually identifies issues retrospectively or at a scheduled milestone. |
| Coverage | Can test entire transaction populations when data are available. | Uses targeted procedures and can examine non-transactional controls, governance and qualitative evidence. |
| Independence | Often owned by management or an operational risk team. | Independent audit or control testing provides stronger assurance. |
| Detection logic | Strong for known indicators, thresholds and repeatable patterns. | Can challenge assumptions, assess control design and investigate novel schemes. |
| Cost and burden | Requires data integration, rule or model maintenance, triage and investigators. | Requires planning, skilled staff and evidence collection. |
| Deterrence | Deters when staff believe detection and response are credible and timely. | Scheduled, targeted or surprise work can increase perceived scrutiny. |
| Adaptability | Rules and models can be changed quickly as patterns emerge. | Provides structured learning and independent validation for strategy changes. |
What the evidence says about effectiveness
Federal evaluation practice in the United States
The U.S. Government Accountability Office surveyed 24 federal agencies in 2023 and reported in Combating Fraud: Approaches to Evaluate Effectiveness and Demonstrate Integrity (2026) that agencies need to evaluate and adapt fraud-risk activities with multiple metrics and stakeholder input. Its warning is operationally important: “A third didn’t have regular monitoring or evaluation activities.” GAO also found that “Half didn’t regularly make changes based on evaluation results.” Monitoring without evaluation and adaptation can therefore leave an agency measuring effort without improving its controls.
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GAO’s framework has four connected components: organizational commitment, risk assessment, control activities, and evaluating and adapting fraud-risk management. Monitoring and feedback are ongoing practices across those components, not a substitute for the other three.
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International strategy and evaluation guidance
The OECD’s Evaluating, Updating and Monitoring Anti-Fraud Strategies (2026) states that “Monitoring and evaluation systems are most effective when they are designed early in the strategy cycle.” The guidance distinguishes the functions:
- Monitoring supplies continuous feedback on implementation and indicators.
- Evaluation assesses relevance, coherence, effectiveness, efficiency, impact and sustainability.
Robust systems use measurable indicators, reliable baselines, regular proportionate reporting and independent validation. A mid-term evaluation supports corrective adjustments; an end-term evaluation captures lessons for the next strategy cycle. That distinction matters when an agency calls a continuously running analytics process an audit: frequency does not create independence or prove impact.
Public-sector measurement examples from the United Kingdom
The UK Public Sector Fraud Authority reported the following 2023/24 figures in 2026. Each headline combines fraud and error, so it should not be read as fraud alone:
| Measure | Amount | Qualification |
|---|---|---|
| Detected fraud and error | £1.7 billion | UK public sector, reporting year 2023/24. |
| Recovered fraud and error | £770 million | UK public sector, reporting year 2023/24. |
| Prevented fraud and error | £413 million | UK public sector, reporting year 2023/24. |
Detection increased 27% in 2023/24 compared with 2022/23. The PSFA cautions that prevention trends are not directly comparable because reporting guidance changed and estimated or modelled savings became subject to assurance. A higher prevention figure can therefore reflect methodology as well as operational performance.
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The PSFA estimated £51.3 billion to £81.0 billion of fraud and error for 2022/23 outside COVID-19 schemes. That range represented 3.0% to 4.8% of government expenditure and income. It was an estimate before intervention, not a statement of actual loss. Agencies should disclose scope, year and method whenever they present comparable figures.
Population testing and proactive detection
World Bank internal-audit guidance (2018) advises auditors to “Test entire populations and avoid losing the information in samples.” It also describes “Proactive fraud detection by running repetitive or continuous analysis and engaging in real time testing.” Alerts on potential fraud or control breaches can act as a preventive measure when people know that these routines operate. The guidance supports using monitoring where population data and response capacity are strong, while retaining audit work for assurance and issues that analytics cannot represent.
What behavioral experiments can—and cannot—show
An Internal Audit Foundation research summary (2012) described two multi-period experiments comparing continuous and periodic auditing. Continuous auditing reduced perceived opportunity more than periodic auditing only when the actual probability of detection was high. When the probability was low, periodic auditing performed better on that perception measure. The experiments did not find corresponding effects on actual fraudulent behavior.
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Why continuous monitoring can fail
Alerts are not investigations
A rule that flags every payment to a newly created vendor may be sensitive but produce a queue too large for investigators. If staff routinely close alerts without evidence, users learn that the control is symbolic. Agencies should set service levels for triage and escalation, record reasons for closure and review false-positive rates.
Data quality limits coverage
Monitoring cannot test fields that are missing, late, inconsistent or deliberately manipulated. Before enabling a rule, document the source system, refresh interval, completeness checks and the transaction populations it excludes. A whole-population claim is valid only for the population actually ingested and tested.
Static logic misses changing schemes
Fraud indicators evolve. Thresholds, vendor behavior and payment routes that were unusual last year may become common, while a new scheme may not match an existing rule. Periodic independent review should challenge assumptions, examine overrides and authorize updates to rules or models.
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When the same team approves payments, owns the monitoring dashboard and closes alerts, conflicts can arise. Assign alert ownership, escalation authority and independent review explicitly. Periodic audit or control-testing functions should be able to inspect the monitoring process itself.
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A practical operating model for a public body
- Map fraud risks. Identify high-value, high-velocity and high-vulnerability transaction streams. Include grants, procurement, payroll, benefits, refunds and payments made through intermediaries where they are in scope for the agency.
- Choose populations for continuous testing. Apply rules or models to whole populations when data quality and response capacity are adequate. For each control, document the threshold, alert owner, escalation time, evidence required and treatment of false positives.
- Keep independent audits and targeted tests. Schedule work that examines control design, overrides, segregation of duties, third parties, governance and non-transactional risks. Use surprise testing where the risk assessment supports it.
- Connect alerts and findings. Use a common case-management and remediation process so an alert, an audit exception and a confirmed loss can be linked to the same root cause, owner and due date.
- Review the strategy on a defined cycle. Examine indicators at least at the mid-point of the strategy cycle and again when the strategy is renewed. Preserve baselines and record any change in definitions, data, assurance or estimation methods.
- Report activity and outcomes. Report alerts, audits and investigations alongside prevented amounts, recoveries and residual loss. Obtain independent validation where feasible and explain what each measure includes.
What to measure
A useful scorecard separates work performed from results achieved. Activity metrics show whether the control is operating; outcome metrics show whether risk is changing.
| Metric group | Examples | Interpretation |
|---|---|---|
| Monitoring activity | Transactions tested, alerts generated, median time to triage, escalation timeliness and false-positive rate. | Shows reach, workload and operating discipline; it does not prove prevented loss. |
| Audit activity | Audits completed, controls tested, exceptions by severity and overdue remediation actions. | Shows assurance coverage and whether management addresses findings. |
| Enforcement and case outcomes | Investigations opened and closed, substantiated cases, referrals, recoveries and disciplinary or procurement actions. | Shows follow-through from signal to consequence. |
| Financial outcomes | Prevented, recovered and residual loss, with the population, period and estimation method stated. | Supports decision-making only when definitions and methodology remain comparable. |
| Control improvement | Rules changed, process changes implemented, repeat findings and time to close root causes. | Shows whether evaluation changes the system rather than merely documenting problems. |
Keep a baseline before changing a rule or process. If a definition, data source or assurance method changes, mark the break in the series instead of presenting the figures as a seamless trend.
Choosing the right cadence
| Risk condition | Emphasis | Reason |
|---|---|---|
| High-value or high-velocity payments with reliable, timely data | Continuous monitoring plus rapid investigation. | Early alerts can limit accumulation of losses. |
| Complex procurement, third-party delivery or weak process documentation | Targeted independent audits supported by monitoring. | Judgment, contracts, governance and control design require evidence beyond transaction fields. |
| New program or major system change | Baseline assessment, frequent monitoring and an early independent review. | New risks and data defects are more likely before controls mature. |
| Low-volume or slow-moving activity | Risk-based periodic testing, with monitoring where a reliable signal exists. | Continuous tooling may cost more than the exposure justifies unless the risk is severe. |
| Repeated alerts with few substantiated cases | Independent review of rules, data and investigator decisions. | High noise can hide real cases and create false assurance. |
These are risk-based choices, not fixed legal intervals. The agency’s fraud-risk assessment should set the cadence and document why it is proportionate.
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- Calling analytics an audit: reserve the term audit for work with a defined scope, evidence procedures and appropriate independence; describe a management dashboard as monitoring.
- Optimizing for alert volume: track substantiation, response time, recovery and repeat findings, not just the number of alerts.
- Ignoring closed-alert quality: sample dispositions and require evidence for closure so investigators cannot make the queue disappear without learning.
- Leaving contractors outside the control picture: include controls operated by contractors or other public bodies in independent field testing where they affect the agency’s risk.
- Reporting estimates as losses: distinguish detected, prevented, recovered, estimated and residual amounts, and state whether figures include error as well as fraud.
- Failing to adapt: set a formal review point at mid-cycle and strategy renewal; assign an owner and deadline for every approved change.
Bottom-line decision rule
Use continuous transaction monitoring when the agency has timely, complete data and the capacity to investigate alerts. Keep periodic independent audits to test whether the monitoring and wider control system are designed well, operating as intended and addressing risks outside transaction patterns. Judge the combination by detection quality, credible follow-through, prevented and recovered amounts, residual exposure and independently validated learning—not by how often a dashboard refreshes.
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