Data Analytics Test Selector Tool

Generic analytics scripts produce results that do not answer an audit question. This tool helps auditors choose analytics that directly test a risk, linking the risk hypothesis to a test, the data fields required, the expected exception pattern, and whether the test suits one-time audit work or continuous monitoring.

Use it when designing analytics for an audit, requesting data from process owners, building continuous-monitoring routines or deciding which tests are worth automating. The core inputs are the risk hypothesis, process or transaction type, available datasets, key fields, expected pattern, population volume, refresh frequency and data-quality constraints. The decision matrix maps risk patterns to example tests and monitoring fit: duplicate invoices or payments, transactions just below approval limits, weekend or after-hours activity, recent bank changes before payment, and unusual price, quantity or claim outliers. The working sheet records test logic, expected exceptions, validation needed, frequency and the owner for follow-up.

The worked example tests whether employees split expenses to stay below approval thresholds, by finding same employee, merchant and day combinations whose combined value exceeds the threshold, then confirming legitimate multi-receipt cases, with monthly monitoring if claim data is consistently available.