Process Mining for Auditors

Process Mining for Auditors: See What Actually Happened

Compare event data from completed cases with an approved process model. Find deviations, inspect the case histories behind them, and export evidence for review. This analysis supports your audit work; it does not replace your judgment or certify compliance.

What evidence does process mining produce?

A conformance test compares recorded process execution with the standard you define. The results show which cases followed the expected path and where they differed. Use this process conformance evidence to focus your review on exceptions instead of reconstructing every case by hand.

The evidence depends on the event data and process standard you provide. A difference between recorded activity and the defined control does not explain why it occurred or prove that a control failed. You assess what the finding means.

Learn how Process Mining supports conformance checking.

How do you trace a finding to its source case?

Start with a deviation in the analysis and inspect the case-level process history behind it. Move from the summary finding to the recorded events for that case, then review their sequence and timing in context.

To make results easier to review, retain relevant case identifiers and source records with your export. Your event data needs the activity records, timestamps, and case references required to trace execution back to the source.

What can you export, and what should you keep with it?

After reviewing the deviations, export the findings and supporting evidence for your audit file. Keep the export with the approved process model, test scope and period, and references to the source data used in the analysis.

A deviation list is difficult to assess without this context. ProcessMind provides evidence for your review; you decide whether it is sufficient for the audit.

How should you record and assess exceptions?

A deviation is a difference between recorded execution and the process model you are testing against. It may indicate a skipped activity, an unexpected sequence, or another departure from the defined path.

Record the exception, case evidence, and your assessment separately. The analysis can help you find and investigate variations, but it cannot determine whether an exception is justified, a control breach, or a compliance issue. That assessment requires your judgment and the relevant organizational context.

How do you run a conformance test?

1. Choose the process and control question. Define what you want to test, the period in scope, and the approved process standard.
2. Prepare the event data. Include the case identifiers and activity records needed to trace execution to source cases.
3. Compare execution with the standard. Run a conformance check and review the deviations it identifies.
4. Investigate exceptions. Open the relevant case histories, check the source records, and document your assessment.
5. Export the evidence. Keep the findings, case references, process model, and test scope together for review.

Read the process governance guide to learn how to define and maintain process standards.

What does a conformance test look like in practice?

Suppose your approved process requires a request to be submitted, reviewed, and approved before payment. Model that sequence, then compare it with event data from completed cases.

The analysis can flag cases where recorded activity differs from the model, such as a payment recorded before approval. Inspect the case history and trace the finding to its source records. Then assess whether the sequence reflects a control exception, a data issue, or an approved variation, and document your conclusion for review.

The result is evidence of process conformance, not an automatic compliance decision.

How can process mining help with audit preparation?

Process mining can help you find deviations across available cases, rather than relying only on a manually selected sample. Use the results to focus your investigation, organize evidence around case histories, and repeat the same test when reviewing another period.

Coverage depends on the completeness and quality of your event data. Missing events, inconsistent case identifiers, or an incomplete process model can affect the results. Validate the data and standard before relying on your findings.

How does this relate to ISO 9001 and DORA?

For ISO 9001 process documentation, a defined process model can serve as the standard for comparing recorded execution. The analysis can help you find where actual cases differ from that model. By itself, it does not establish that your documentation or quality management system meets ISO 9001 requirements.

For DORA operational resilience evidence, process data may help you examine recorded activity related to ICT processes and incidents. Whether the evidence meets your obligations depends on the requirement, the available records, and your assessment. Process mining does not certify DORA compliance.

See the life sciences compliance use case for another example of process analysis in a regulated setting.

What should you check before relying on the results?

Before using an export in an audit, confirm that:

• The process model reflects the approved standard for the period under review.
• The event data covers the cases and activities in scope.
• Case identifiers let you trace findings to source records.
• You have documented the test scope and any data limitations.
• You have assessed exceptions instead of treating every deviation as a control failure.

Start with one process and one clearly defined control question. Then assess whether the case-level findings and evidence export meet your audit needs.

Run one conformance test on real cases: /freetrial