A defensible, Yellow Book–aligned process is necessary for assessing the reliability of computer-processed data. Using a structured, risk-based approach, you'll learn to plan, test, conclude, and report so your audits rest on complete, accurate, and valid evidence.
Overview
Syllabus
Module 1: Government Audit Standards, Policies, and Guidelines
- Review GAO Government Auditing Standards (Yellow Book) requirements for sufficient, appropriate evidence and overall assessment of evidence.
- Understand when and how to evaluate information systems (general, application, and user) controls that affect data reliability.
- Apply guidance on using the work of others and specialists, and documenting qualifications, scope, and quality.
- Identify required report content (objectives, scope, methodology) and how to disclose limitations and uncertainties.
Module 2: Data Reliability Considerations
- Define data reliability (completeness, accuracy, validity, and consistency) and why it matters for audit findings.
- Recognize common forms of computer-processed data (extracts, enterprise systems, spreadsheets, surveys) and typical reliability issues.
- Use computer-assisted audit techniques (e.g., logical tests, duplicate checks, range and date tests) to evaluate sufficiency and appropriateness.
- Understand common problems (incomplete, untimely, incorrect, or incompatible data) and their causes.
Module 3: Overall Framework for Assessments
- Decide whether a data reliability assessment is needed based on planned use and risk.
- Scope the extent of assessment using expected importance, corroborating evidence, and risk of using the data.
- Focus effort on portions of data relevant to audit objectives; consider leveraging information/system control reviews when efficient.
- Follow the framework stages: determine need and plan, conduct work, make the determination, and include appropriate report language.
Module 4: Planning and Performing the Assessment
- Initiate reliability work early; determine timing, level of detail (record- vs. summary-level), and documentation needs.
- Collect existing information: interview knowledgeable officials; obtain data dictionaries, system docs, and prior reviews.
- Test data (counts, missing values, duplicates, ranges, identifiers, dates, relationships) and, when needed, trace to/from source documents.
- Document plans, procedures, results, and conclusions clearly, using provided planning and summary worksheets.
Module 5: Documenting and Reporting Assessment Results
- Synthesize testing and control information into an overall reliability determination tied to audit objectives.
- Disclose limitations/uncertainties, describe data sources and methods, and explain population, period, and sampling as applicable.
- Tailor report wording so users can reasonably interpret findings without being misled; describe any constraints on scope or access.
Module 6: Structured Approach for Assessing Reliability of Data
- Apply a flexible, risk-based approach aligned with GAO’s Assessing Data Reliability guidance.
- Leverage existing information, involve stakeholders, and perform only the work necessary to conclude “use or not.”
- Use standardized tools (planning templates, documentation requests, and example data tests) to streamline assessments.
Module 7: Case Study
- Work through a realistic scenario to plan, test, and conclude on data reliability.
- Practice documenting decisions, communicating limitations, and drafting appropriate report language.
Taught by
Mark Gebicke, Penny Popps, and Lyndon S. Remias