What are assurance services?
Assurance services are independent professional engagements—most commonly delivered by certified accountants such as certified public accountants (CPAs) or chartered accountants—that increase the reliability of information used for decisions. Rather than preparing the information, the assurance provider examines it and issues a conclusion about its credibility, completeness or accuracy. The objective is to reduce “information risk,” the chance that decision-makers are using wrong or misleading data.
Core ideas and why they matter
– Independence: The provider must be seen as impartial so users can trust the conclusions.
– Decision focus: Assurance is intended to improve the quality of information that managers, investors, or partners rely on.
– Scope variety: Assurance applies to financial and non-financial topics—anything from a spreadsheet formula to an organization’s risk profile.
– Standards: Specialist guidance exists (for example ISAE 3000 and professional sourcebooks) to help practitioners design and report engagements.
Types of assurance services (common categories)
– Risk profile reviews: Confirm whether an organization has identified material risks and has suitable controls.
– Performance measurement assurance: Test whether performance metrics (a “balanced scorecard”) are relevant and measured reliably.
– Information systems reliability: Verify that internal IT and reporting systems produce accurate, timely data.
– E‑commerce systems assurance: Evaluate data integrity, security, privacy and reliability of online transaction and customer-facing systems.
– Healthcare performance assurance: Assess whether providers, hospitals or plans deliver effective, safe and accessible care under new payment models.
Typical engagement process (step‑by‑step)
1. Accept engagement and confirm independence and competence.
2. Define scope and reporting objective (what users want to know).
3. Plan procedures based on assessed risk (where errors are most likely).
4. Gather evidence (testing controls, recalculating figures, inspecting documentation).
5. Evaluate results against criteria and professional standards.
6. Issue a written conclusion or assurance report and agree follow-up actions.
Short checklist — hiring or commissioning assurance services
– Purpose: Are you seeking assurance on accuracy, completeness, controls, or compliance?
– Provider credentials: Is the firm licensed (CPA/chartered) and experienced in the subject area?
– Standards and framework: Will the engagement follow ISAE 3000, local assurance guidance, or another recognized standard?
– Scope and deliverables: Is the scope, timeline and form of report (assurance opinion vs. limited assurance) clearly stated?
– Independence and conflicts: Can the provider act independently from the subject entity?
– Evidence approach: Does the plan specify sampling, testing methods and evidence thresholds?
– Follow‑up: Will the provider offer remediation recommendations and a timeline for re‑testing?
Worked numeric example — checking a mortgage calculator
Scenario: A mortgage website shows monthly payment for a $200,000 mortgage, 30 years, 4% annual interest. You (or an assurance practitioner) can quickly recompute the standard amortizing payment to check the site.
Formula for monthly payment (annuity formula):
Payment = r × PV / [1 − (1 + r)^−n]
Where:
– PV = loan principal = 200,000
– r = monthly interest rate = annual rate / 12 = 0.04 / 12 ≈ 0.0033333
– n = total months = 30 × 12 = 360
Calculation:
– Numerator = r × PV = 0.0033333 × 200,000 = 666.6667
– Discount factor denominator = 1 − (1 + r)^−n ≈ 1 − (1.0033333)^−360 ≈ 0.6982
– Payment ≈ 666.6667 / 0.6982 ≈ $954.83
Interpretation: If the mortgage site reports a monthly payment materially different from $954.83 (for example $1,050), an assurance reviewer would flag a roughly 10% discrepancy and investigate whether the site used the wrong formula, rounding, fees, or input assumptions.
Standards and guidance
Professional assurance work follows recognized guidance so users can compare reports. Internationally applicable guidance for non‑audit assurance is ISAE 3000; many professional bodies publish additional practical guidance and sourcebooks for practitioners. Regulatory changes (for example, post‑2002 laws aimed at investor protection) have also increased demand for independent assurance on financial and control information.
When assurance is especially useful
– When third parties (investors
When assurance is especially useful — When third parties (investors, lenders, regulators, customers, or potential acquirers) depend on information produced by an organization, an independent assurance engagement can increase trust and reduce information risk. Common situations:
– Capital raising and lending decisions — Lenders and investors often ask for assurance on financial statements, forecasts, or covenant calculations.
– Mergers, acquisitions, and divestitures — Buyers request assurance on due-diligence schedules, pro forma adjustments, or working-capital calculations.
– Regulatory compliance — Firms subject to rules (tax, environmental, safety, financial reporting) use assurance to demonstrate compliance.
– Outsourcing and service providers — Customers of cloud, payroll, or payment processors ask for SOC (System and Organization Controls) reports or similar assurance on controls.
– Internal control and risk management — Management obtains assurance to validate control design and operating effectiveness before public reporting or certification.
– Nonfinancial reporting — Sustainability, carbon, and ESG (environmental, social, governance) claims increasingly receive independent assurance to support public disclosures.
– Performance metrics and KPIs — Assurance on key performance indicators supports executive compensation, vendor payments, or regulatory filings.
Types of assurance and typical conclusions
– Reasonable assurance (high level of assurance): The practitioner forms an opinion that the subject matter is, in all material respects, in accordance with the criteria. This opinion is typically expressed positively (for example, “In our opinion…”). It requires more extensive procedures and evidence.
– Limited assurance (moderate level of assurance): The practitioner issues a conclusion expressed negatively (for example, “Nothing has come to our attention that causes us to believe…”). Procedures are narrower and evidence is less extensive than for reasonable assurance.
– Agreed-upon procedures (AUP): The practitioner performs specific procedures agreed with the client and reports factual findings. No overall opinion or conclusion is provided; users draw their own conclusions from the reported findings.
Key terms (defined)
– Subject matter: The information or phenomenon being examined (for example, a set of financial statements, an ESG metric, or control operating effectiveness).
– Criteria: The benchmarks used to evaluate the subject matter (for example, GAAP for financial statements or a specified greenhouse-gas accounting standard).
– Assertion: A representation, usually made by management, about the subject matter (for example, that controls are operating effectively).
– Independence: The practitioner’s lack of bias or conflict of interest that could reasonably impair objectivity.
Typical assurance engagement process (step-by-step)
1. Engagement acceptance and preconditions
– Confirm the practitioner’s independence and competence.
– Agree on the subject matter, criteria, scope, timing, fees, and reporting deliverable in an engagement letter.
2. Planning and risk assessment
– Understand the entity, relevant industry, and internal control environment.
– Identify areas of higher risk where misstatement or control failure is more likely.
3. Design procedures
– Select procedures appropriate to the level of assurance (inquiry, inspection, observation, recalculation, confirmation, analytical procedures, re-performance).
4. Obtain evidence
– Execute planned procedures, document workpapers, and evaluate quality and sufficiency of evidence.
5. Evaluate results and form conclusion
– Assess whether the evidence supports the intended assurance conclusion. If significant issues arise, request management explanations and, if necessary, additional procedures.
6. Reporting
– Prepare an assurance report that includes scope, criteria, procedures performed (or a description of work), the conclusion/opinion, and any identified exceptions or limitations.
Checklist for selecting an assurance provider
– Qualifications and experience in the specific subject matter (financial, IT, sustainability, etc.).
– Independence policies and conflict-of-interest safeguards.
– Familiarity with relevant standards and criteria (e.g., ISAE 3000 for non‑audit assurance).
– Sample reports and references from similar engagements.
– Proposed scope, methodology, timelines, and fee estimate.
– Data security and confidentiality provisions.
Sample language (illustrative only)
– Reasonable assurance: “In our opinion, the accompanying [subject matter] is presented fairly, in all material respects, in accordance with [applicable criteria].”
– Limited assurance: “Based on our limited procedures, nothing has come to our attention that causes us to believe that the accompanying [subject matter] is not presented fairly, in all material respects, in accordance with [applicable criteria].”
– Agreed-upon procedures: “We performed the procedures agreed upon with [specified parties] and report our factual findings below. We do not express an opinion or conclusion.”
Worked example — Scope choice and evidence volume (illustrative)
– Scenario: A mid-size company requests assurance on a payroll control that calculates employee benefits.
– Option A (reasonable assurance): Practitioner tests design and operating effectiveness for a full quarter. Procedures include re-performance of the calculation for a
…full quarter (13 weekly payroll runs). For each run the practitioner re-performs the benefit calculation for a 10% sample of employees (population = 2,000 employee-payroll events; sample = 200). Additional procedures include walkthroughs of the payroll system, inspection of control configuration, and confirmation of benefit rates with HR. Total evidence: 13 runs × 200 re-performances = 2,600 re-performed calculations; plus system logs, HR confirmations, and exception testing. Estimated time: 40–60 practitioner-hours. Estimated cost: depends on hourly rates; use this to budget.
Option B — Limited assurance
– Scope: shorter period or fewer transactions; emphasis on inquiry, analytical review, and limited re-performance.
– Procedures (illustrative): inquiries of payroll manager; review of exception reports for the quarter; analytical comparison of benefits expense by pay-period vs. prior quarter; re-performance of the calculation for a targeted high-risk sample of 50 employee-payroll events across the quarter.
– Total evidence: analytical ratios, 50 re-performances, walkthrough notes, and one control re-test.
– Time: 12–20 practitioner-hours. Lower cost and less persuasive evidence than reasonable assurance.
Option C — Agreed-upon procedures
– Scope: specific procedures agreed with the client or other users; deliverable is factual findings, not an opinion.
– Procedures (illustrative): perform the calculation for 20 named employees for the most recent payroll run; extract system access logs for two payroll administrators over the quarter; provide a list of exceptions discovered and sampled supporting documents.
– Total evidence: discrete factual tests and copies of supporting documents.
– Time: 8–12 practitioner-hours. Suitable when users only need factual confirmation of particular items.
How to choose the level of assurance — practical checklist
1. Identify the user(s) and their decision use (e.g., regulator, lender, management). If users need a formal opinion, choose reasonable or limited assurance.
2. Determine materiality (the magnitude at which misstatement changes decisions).
3. Assess inherent and control risk (higher risk favors reasonable assurance).
4. Consider timeframe and budget constraints.
5. Confirm reporting expectations (opinion vs. factual report).
6. Select procedures that can reasonably address the stated objective.
Sampling and evidence sizing — worked numeric example (detecting errors)
Objective: detect at least one error with 95% confidence when the expected error rate is 1% across N transactions.
Attribute-sampling approximation (probability-model):
n ≈ ln(1 − confidence) / ln(1 − expected_error_rate)
Example: confidence = 95% (0.95); expected_error_rate = 1% (0.01)
n ≈ ln(1 − 0.95) / ln(1 − 0.01) = ln(0.05) / ln(0.99) ≈ (−2.9957) / (−0.01005) ≈ 298
Interpretation: test about 298 items to have ~95% probability of finding at least one error if the true error rate is 1%. If expected error rate is higher (say 5%), required n drops:
n ≈ ln(0.05) / ln(0.95) ≈ 59.
Notes and assumptions:
– This calculation aims only to detect at least one error; it does not estimate population error rate or support an opinion on controls by itself.
– For finite populations, adjust using hypergeometric methods or use statistical sampling tables.
– Confidence level, tolerable deviation, and expected error rate are judgmental inputs—document assumptions.
Evidence types and practical examples
– Inquiry: documented answers from responsible personnel (useful but low persuasiveness).
– Inspection: screenshots, reports, contracts, payroll registers (highly persuasive when original).
– Re-performance: practitioner independently recalculates amounts (high persuasiveness).
– Observation: watching control being performed (useful for operating effectiveness).
– Confirmation: external confirmations (e.g., insurer or trustee confirmations).
Preparation checklist for entities requesting assurance
1. Define the subject matter and criteria (e.g., payroll benefits calculated per policy X).
2. Identify intended users and intended use of report.
3. Choose level of assurance and document rationale.
4. Assemble supporting documentation and system extracts before fieldwork.