Financial
Financial Misstatement Likelihood
Modelled likelihood of misstatement by account balance, weighting volume, complexity and control strength.
Why misstatement risk should be modelled, not guessed
Audit effort is finite, so directing it toward the account balances most likely to be misstated is the difference between an efficient audit and a superficial one, a principle embedded in ISSAI and the audit risk model. Likelihood depends on transaction volume, account complexity and the strength of relevant controls, not on materiality alone. AuditPro Core models misstatement likelihood by account balance so planning concentrates scrutiny where the risk genuinely lies.
The Numbers
AuditPro Core renders this view from your tenant's live, tamper-evident records. The figures below are illustrative sample data.
Balances assessed
52
High likelihood
9
17%
Avg control strength
3.2
of 5
R value at risk
R 1.8 bn
Misstatement likelihood by balance
Likelihood drivers by balance
| Balance | Value | Complexity | Likelihood |
|---|---|---|---|
| Property & equipment | R 14.2 bn | 4.5 | 4.2 |
| Receivables | R 3.6 bn | 3.8 | 3.9 |
| Provisions | R 0.9 bn | 4.1 | 3.6 |
| Revenue | R 8.4 bn | 3 | 3.1 |
| Payables | R 2.1 bn | 2.2 | 2.4 |
Figures shown are illustrative sample data for demonstration. AuditPro Core renders these views from your own tenant's live, tamper-evident records.
Drivers of misstatement
Misstatement likelihood rises with high transaction volume, accounting complexity and estimation. These factors increase the chance an error arises and survives undetected.
Control strength as a counterweight
Strong controls reduce the likelihood that an inherent error becomes a misstatement. The model weighs control reliability against the inherent drivers for a net view.
Balance-level focus
Risk is uneven across the financial statements. Modelling at the account-balance level reveals which areas, such as estimates or high-volume revenue, warrant the most testing.
Likelihood versus materiality
A material balance is not automatically high risk, and a smaller balance can be. Combining likelihood with materiality gives a sharper basis for scoping than either alone.
How AuditPro Core Bridges the Gap
- Risk modelling: volume, complexity and control strength are combined into a likelihood score per balance.
- Scoping support: the platform ranks balances so audit and management attention follows modelled risk.
- Continuous monitoring: scores update as control assessments and transaction patterns change.
- Traceability to source: each score links to the controls and data that informed it.
Key Takeaways
- Direct testing by modelled likelihood, not by balance size alone.
- Volume, complexity and estimation drive misstatement risk upward.
- Strong controls offset inherent risk in the net likelihood view.
- Combine likelihood with materiality for sharper audit scoping.
See This on Your Own Data
AuditPro Core renders this dashboard from your tenant's live, tamper-evident records — every figure traceable to source.