Xero fraud-risk review
Apply the seven Audit Analytics analyses to supported Xero accounting populations and drill from chart exceptions into the records used by the test.
Read the Xero guide →Internal fraud-risk review
Use accounting-data patterns to investigate internal fraud risk—not to accuse people
Internal theft and fraud can appear in accounting data as unusual values, repeated transactions, reversals, period-end postings or uncommon counterparties. Datplan Audit Analytics helps reviewers surface those patterns in supported Xero and QuickBooks data and then inspect the records behind the result.
The useful distinction
An exception is a question, not a conclusion
Fraud-risk analytics should identify records that deserve attention. A duplicate-looking payment may have a valid explanation; a round amount may be a normal fixed fee; a reversal may be routine correcting activity. The reviewer still needs the accounting context, source documentation, approval history and other evidence needed to understand what happened.
That is why Datplan pairs each Audit Analytics chart with Audit Evidence drill-down: the chart is a route into the underlying records rather than a verdict.
Seven different lenses
Different fraud risks create different accounting patterns
No single test is a universal fraud detector. The value comes from selecting analyses that fit the population and then corroborating what they surface.
| Analysis | Pattern it can surface | Why follow-up matters |
|---|---|---|
| Benford's Law | First- or second-digit frequencies that depart from the expected distribution in a suitable population. | The population may simply be unsuitable for Benford analysis. |
| Exceptional values | Largest transactions meeting a selected threshold. | High value can be completely legitimate and may already have enhanced approval. |
| Period-end activity | Concentrations of postings close to month end. | Normal accruals, cut-off processes and reporting routines can explain the pattern. |
| Round amounts | Values close to selected round-number multiples or tolerances. | Fixed fees and standard pricing can naturally create round values. |
| Possible duplicates | Records sharing counterparty, date and amount, optionally including reference matching. | Repeated legitimate purchases or split processing can resemble duplicates. |
| Post-period reversals | Opposite-value entries matching within a bounded period after period end. | Legitimate accrual reversals and corrections are common. |
| Rare high-value counterparties | Large transactions involving counterparties seen only infrequently. | A one-off supplier, asset purchase or exceptional transaction may be expected. |
A disciplined review
Move from population to evidence
- Define the risk questionDecide what type of unusual activity matters for the review rather than running every test without purpose.
- Select the population and periodUse the relevant supported Xero or QuickBooks accounting data and a period that matches the question.
- Configure the analyticSet thresholds, period-end windows, tolerances or duplicate criteria as appropriate.
- Review the chartLook for concentrations, outliers or groups that warrant inspection.
- Open Audit EvidenceInspect the records used by the analysis and reconcile them to the source context.
- CorroborateUse approvals, invoices, receipts, accounting-platform history and other engagement evidence before deciding what the exception means.
Examples of follow-up questions
- Was the transaction authorised by the expected person?
- Is there valid source documentation for the amount and counterparty?
- Does a possible duplicate represent a second payment or a legitimate repeated purchase?
- Was a period-end posting reversed appropriately and for a documented reason?
- Is an unusual supplier genuinely new, or is there a master-data or coding issue?
- Does the accounting platform's own audit history support the explanation?
Xero and QuickBooks
The same seven analyses across both accounting sources
Datplan keeps the conceptual audit-test set consistent across supported Xero and QuickBooks populations, while the available source records and fields remain dependent on each provider.
QuickBooks fraud-risk review
Use the equivalent seven analyses on supported QuickBooks data and treat them as complementary to the QuickBooks Audit Log, source documents and control evidence.
Read the QuickBooks guide →Professional and employment boundary. Datplan does not determine whether a person committed fraud, theft or misconduct and should not be used as the sole basis for an allegation, disciplinary decision or audit conclusion. Follow applicable professional, legal, HR and evidential procedures.
Internal fraud questions
Using accounting analytics responsibly
Does an unusual accounting transaction prove employee fraud?
No. An unusual value, duplicate, reversal or period-end posting is an indicator for investigation, not proof of fraud, error or intent. Review source documents, approvals, accounting-system history and other evidence before reaching a conclusion.
Can Datplan review internal-fraud indicators in both Xero and QuickBooks?
Yes. The Audit Analytics area uses the same seven analyses for supported Xero and QuickBooks populations, with Audit Evidence drill-down to the records used by each analysis.
Which Datplan tests may be relevant to internal fraud risk?
Possible duplicates, exceptional values, round amounts, period-end activity, post-period reversals, rare high-value counterparties and Benford analysis can each surface different patterns. The relevance of a test depends on the population and the risk being assessed.
Does Datplan replace the accounting platform's audit trail or an auditor's procedures?
No. Datplan provides transaction-pattern analytics and evidence drill-down. It does not replace Xero or QuickBooks audit-history features, source documents, approvals, professional judgement or procedures required by an audit standard.
Review the accounting evidence behind unusual patterns
Use Datplan Audit Analytics with supported Xero or QuickBooks data, then investigate the records behind each result before reaching a conclusion.