More operations reviewed
Where appropriate, analytics replaces sampling with full-population testing and improves audit selection.
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Internal audit development
Internal audit that delivers better assurance while asking less of the business
Digital maturity assessment, a practical development programme, and implementation of analytics together with the internal audit team.
Digital maturity profileassessment example
CurrentTarget
Data access35 → 75
Analytics45 → 80
Workflow55 → 75
Reproducibility30 → 85
Skills50 → 80
AI governance20 → 65
The target depends on the function’s mandate, team, systems, and risks.
Value for the company
Broader coverage. Faster reviews. Fewer requests to the business.
Analytics creates value when it changes auditors’ daily work and improves the information available to leadership.
Reproducible conclusions
The link from source data to result is preserved, while calculations can be refreshed and reviewed quickly.
Less management effort
Repeatable access and scheduled extracts reduce manual collection, duplicate requests, and waiting for information.
Assessment model
Digitalisation ≠ the number of dashboards
The function is assessed across connected capabilities. Improvements are selected based on value, complexity, and organisational readiness.
Data access
Sources, permissions, extraction frequency, data quality, and consistency of reference data.
Analytics
Scenarios for planning, testing, and continuous monitoring rather than isolated calculations.
Workflow
A clear link between risk, control, test, evidence, conclusion, and action.
Reproducibility
Versioned logic, repeatable calculations, and a reviewable path from data to conclusion.
Skills
The team’s ability to work with data, formulate hypotheses, and explain analytical results.
AI governance
Clear use rules, confidentiality safeguards, and professional judgement remaining human.
Engagement formats
Assessment or implementation with the team
Digital maturity assessment
Interviews and review of current practices, systems, workpapers, and available data using a structured proprietary scale.
- current and target state profile
- priorities based on value and complexity
- roadmap and requirements for data and skills
Outcome: a grounded development plan with a clear sequence of actions.
Change implementation
Practical delivery of the agreed roadmap together with internal audit, IT, and data owners.
- connections, scheduled extracts, and data quality controls
- pilot analytical scenarios in live audits
- methodology, tools, and transfer of practice to the team
Outcome: operating changes that the team can sustain independently.
Each next stage is decided based on the results of the previous one.
Data and business effort
Data access should not become another project for management
The approach follows the existing infrastructure: from standardised extracts to direct connections.
- start with available data and the highest-value scenarios
- agreed owners, scope, and frequency for data provision
- automated completeness and quality checks for extracts
- fewer repeat requests to business teams
First step
Start with the question that is holding internal audit back today
Describe the team, typical audit portfolio, available systems, and main constraints. I will propose a practical scope for the initial assessment.