Data Reliability Completeness Accuracy Source Testing Steps
Assess supplied data-source independence, completeness, accuracy, and reconciliation facts against a tolerance for use in further audit work.
Description
Data reliability requires evidence about source, completeness, accuracy and reconciliation.
Data reliability requires evidence about source, completeness, accuracy and reconciliation. Entered facts produce this transparent four-criterion screen.1
The returned values include Reliability assessment, Criteria met, Criteria checked, Within tolerance. The How section below explains the calculation, input rules and interpretation.
When to use Data Reliability Completeness Accuracy Source Testing Steps
Use Data Reliability Completeness Accuracy Source Testing Steps when you need to evaluate the supplied records under the calculation and evidence rules below. No data examination, source verification or actual audit-evidence reliability is established.
Prepare source-backed observations and the applicable engagement policy before entering facts. Use consistent monetary units and periods. Supply all boolean evidence flags explicitly, and treat a successful screen as a reason to continue professional review.
How to use Data Reliability Completeness Accuracy Source Testing Steps and understand its results
- Prepare source-backed observations and the applicable engagement policy before entering facts. Use consistent monetary units and periods. Supply all boolean evidence flags explicitly, and treat a successful screen as a reason to continue professional review.
- Enter accuracyTested, completenessTested, reconciliationDifference, sourceIndependent, tolerance using the field table and calculation rules, then run the tool.
- Read assessment, criteriaMet, criterionCount, withinTolerance. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| accuracyTested | Accuracy tested | boolean | Required |
| completenessTested | Completeness tested | boolean | Required |
| reconciliationDifference | Signed difference between the data and an independent source. | number | Required |
| sourceIndependent | Source independent | boolean | Required |
| tolerance | Tolerance | number; minimum: 0 | Required |
Require three booleans, finite signed discrepancy and nonnegative finite tolerance. Return inclusive reconciliation flag, criterion count 4 and score count. Four gives reliable, two/three conditional, otherwise unreliable.
count=independent+completeTested+accuracyTested+abs(difference)≤tolerance Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| assessment | Reliability assessment | string; one of "conditional", "reliable", "unreliable" |
| criteriaMet | Criteria met | integer; minimum: 0 |
| criterionCount | Criteria checked | integer; minimum: 4 |
| withinTolerance | Within tolerance | boolean |
{
"input": {
"accuracyTested": true,
"completenessTested": true,
"reconciliationDifference": 25,
"sourceIndependent": true,
"tolerance": 50
},
"output": {
"assessment": "reliable",
"criteriaMet": 4,
"criterionCount": 4,
"withinTolerance": true
}
}Limitations and assumptions
No data examination, source verification or actual audit-evidence reliability is established.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing fields without a declared default, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.
Alternative or Complementary methods
Use Evidence Relevance Reliability Two-Axis Lookup: Evidence relevance and reliability describe different dimensions. This implementation combines their entered ratings by addition. For a complementary task, use Log Analysis User Role ITGC Sample Extraction Steps: IT general control (ITGC) log records need several source fields for follow-up testing. This check uses presence flags rather than parsing logs.
References
Similar or alternative tools
- Evidence Relevance Reliability Two-Axis Lookup
Evidence relevance and reliability describe different dimensions. This implementation combines their entered ratings by addition.
- Log Analysis User Role ITGC Sample Extraction Steps
IT general control (ITGC) log records need several source fields for follow-up testing. This check uses presence flags rather than parsing logs.