ISA 530 · Technology

Sample Size Calculator for Technology

Pre-configured sampling guidance for technology audits. Covers SaaS revenue recognition testing, capitalised development cost sampling, and multi-element arrangement analysis with ISA 530 methodology.

ISA 530 · LIVEv2026.04MUS

Sample size, defended.
Not just computed.

Session
0x31EA
Fiscal Year
FY 2026
Confidence
95%
inputs.conf
methodology.conf
README.md
01// engagement— ISA 530.4
02entity_name=
03fiscal_year_end=
04currency=
05public_interest=
06first_year=
09// method— ISA 530.A4–A14
10sampling.method=
11method.rationale=
Method rationale · ISA 530.A4 documentation
14// parameters— ISA 530.7–8
15confidence_level=
16population=
17tolerable_misstmt=€ · TM ≤ PM
18expected_misstmt=€ · EM · optional
19confidence.rationale=
20tm.rationale=
21em.rationale=
Parameter rationales · ISA 530.9 documentation
24// finite_population_correction— optional
25population_item_count=items · FPC applied if >10%
30// objective— ISA 530.6 · what you're testing + what counts as error
31assertion_tested=
32misstatement_definition=
Objective · ISA 530.6 what you test + error definition
35// population_completeness— ISA 530.5(f) · population must be complete
36population.definition=
37completeness_test=
38sampling_unit=
Population · definition + completeness test
40// stratification— ISA 530.A8 · optional; reduces variability
No strata defined. Stratification is optional — add strata if population has very different sub-groups (by $ size, risk, or nature).
48stratification.rationale=
Stratification · ISA 530.A8 (optional)
50// selection_method— ISA 530.8 · how items are selected
51selection.method=
52selection.rationale=
Selection method · ISA 530.8
55// evaluation— ISA 530.12–14 · MLE / tainting
56
Evaluation · ISA 530.12–14 MLE / tainting
65// sensitivity— EM ±20% impact on n
Enter population and tolerable misstatement to see sensitivity.
Sensitivity · EM ±20% impact on n
70// method_comparison— MUS vs Classical
Enter inputs to compare methods.
Method comparison · MUS vs Classical
75// risk_flags— 15-rule engine · regulator deficiency patterns
Enter inputs to run risk analysis.
Risk flags · regulator deficiency intelligence
80// conclusion— ISA 530.15 · narrative evaluation
81conclusion.narrative=
82qualitative_factors=
Conclusion · ISA 530.15 narrative + qualitative
awaiting input·3/8 core fieldsEUR·MUS
previewwp-mus-2026.pdf
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Sample size
Awaiting input
PRIMARY
Sampling interval
Population ÷ n
Top stratum
Items ≥ interval
Max errors
Before exceeding TM
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Professional working paper with engagement header and sign-off fields
Full ISA 530 methodology with paragraph citations
Step-by-step sample size calculation workings
TM and EM sensitivity analysis tables
Method comparison (MUS vs Classical) with rationale
Risk intelligence flags with ISA references
Sample evaluation section with Stringer bound (MUS)
Population selection documentation and checklist
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Sampling Working Paper
ISA 530 (Revised) · ISA 500
1Sampling ParametersISA 530.7–9
2Sample Size CalculationISA 530.A10–A11
3Method RationaleISA 530.A4–A5
4Sensitivity AnalysisTM & EM ±
5Risk IntelligenceISA 530.A2–A8
6Selection MethodISA 530.A12–A14
7Evaluation CriteriaISA 530.14–15
8Documentation ChecklistISA 530.9
Prepared by ________Reviewed by ________Date ________
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Sampling Considerations for Technology

Technology company audits focus heavily on revenue recognition under IFRS 15, particularly for SaaS, licensing, and multi-element arrangements. The combination of subscription revenue, usage-based pricing, and bundled contracts creates complex populations for sampling. Additionally, capitalised development costs under IAS 38 require testing of both the capitalisation criteria and the amortisation calculations.

Sampling focus: Technology

Revenue sampling for technology companies must account for different revenue streams — subscription fees, licence sales, professional services, and usage-based charges may all be present in a single contract. MUS applied to the contract-level revenue population is effective, but the auditor must also sample within contracts to verify that the allocation of the transaction price to performance obligations is correct.

Key sampling considerations

Stratify the revenue population by revenue type (subscription, licence, services, usage) — each stream has different recognition timing and risks under IFRS 15.

Multi-element arrangements require separate testing of the standalone selling price allocation — sample contracts with multiple performance obligations to verify the allocation methodology.

Deferred revenue balances represent a key assertion — sample deferred revenue items to test both the completeness of deferral and the accuracy of subsequent recognition timing.

Capitalised development costs under IAS 38 should be sampled by project — test whether each project meets the six capitalisation criteria and whether time and cost allocations are supportable.

Share-based payment expenses involve employee-level calculations — sample award grants to verify vesting conditions, fair values, and expense recognition over the vesting period.

Frequently asked questions

What are the key sampling considerations for technology audits?
Stratify the revenue population by revenue type (subscription, licence, services, usage) — each stream has different recognition timing and risks under IFRS 15. Multi-element arrangements require separate testing of the standalone selling price allocation — sample contracts with multiple performance obligations to verify the allocation methodology. Deferred revenue balances represent a key assertion — sample deferred revenue items to test both the completeness of deferral and the accuracy of subsequent recognition timing. Capitalised development costs under IAS 38 should be sampled by project — test whether each project meets the six capitalisation criteria and whether time and cost allocations are supportable. Share-based payment expenses involve employee-level calculations — sample award grants to verify vesting conditions, fair values, and expense recognition over the vesting period.
What is the sampling focus for technology?
Revenue sampling for technology companies must account for different revenue streams — subscription fees, licence sales, professional services, and usage-based charges may all be present in a single contract. MUS applied to the contract-level revenue population is effective, but the auditor must also sample within contracts to verify that the allocation of the transaction price to performance obligations is correct.
How does the ISA 530 MUS formula work?
The standard MUS formula is: n = (Population x Confidence Factor) / (Tolerable Misstatement - Expected Misstatement x Expansion Factor). The confidence factor reflects the acceptable risk of incorrect acceptance. Expected misstatement increases the required sample size because the auditor must leave headroom above the expected level before reaching the tolerable threshold.

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