Audit · Live online
Audit Rewired: Technology, Evidence, and the Modern Engagement
Audit Technology
- When
- June 16, 2027
- Format
- Live online · 1 day · Central Time
- CPE
- Up to 8 credits
- Price
- $299 Early-bird pricing coming soon Payable with CPE Today credits · credit packages coming soon
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Proposed Agenda
All times Central Time. Sessions, times and credits may change before the conference.
The Auditor's Tech Stack: What Changed and What It Means for Evidence
Covers full-population testing, continuous auditing, and the tools now sitting between the auditor and the client's data. Explores how the shift reshapes planning, materiality thinking, and where audit effort goes when sampling stops being the constraint.
Learning Objectives
- Analyze the transition from sample-based testing to full-population analysis and its impact on audit risk models.
- Evaluate how continuous auditing tools change the timing and nature of evidence collection throughout the fiscal year.
- Identify the shifts in materiality considerations when every transaction is visible to the audit team.
- Assess the changing requirements for professional skepticism when relying on automated data intermediaries.
- Field of study
- Audit
- Level
- Intermediate
- Prerequisites
- Experience with standard financial statement audit procedures and basic familiarity with data analysis concepts.
- Advance preparation
- None
- Delivery method
- Group Internet Based
Choose one of 2 sessions
Excel and Power Query for Audit Testing
Most audit testing still starts the same way: someone exports data from the client's accounting system, spends an afternoon cleaning it up in Excel, and repeats the whole process next quarter or next year. Power Query ends that cycle. It records every cleanup step so the same preparation runs again with a single refresh, no matter where the data came from. This session shows how to use Power Query to prepare audit data, run common audit tests, and document the work so it holds up in review. This is a practical, show-and-do session built around the tests auditors actually perform. You'll see how to turn a messy client export into a clean, testable dataset, test a journal entry population for gaps, duplicates, and unusual entries, run a three-way match across purchase orders, receipts, and invoices, and apply Benford's Law and stratification to focus your testing. Just as important, you'll learn how to document each step so a reviewer can follow and re-perform the work. You'll leave with a repeatable approach you can apply to your next engagement.
Learning Objectives
- Import and clean audit data into a refreshable Power Query table
- Apply Power Query steps to test a journal entry population for gaps, duplicates, and unusual entries
- Perform a three-way match by merging purchase order, receiving, and invoice data
- Apply Benford's Law and stratification to identify transactions for further testing
- Document query steps so a reviewer can follow and re-perform the test
- Field of study
- Computer Software and Applications
- Level
- Basic
- Prerequisites
- None. A basic working knowledge of Excel is recommended.
- Advance preparation
- None
- Delivery method
- Group Internet Based
Auditing Automated and Cloud Environments
Examines testing when the process runs itself, including service accounts, segregation of duties, change management over automations, SOC reports, and evidence for controls nobody performs.
Learning Objectives
- Identify the unique risks associated with service accounts and automated system permissions.
- Evaluate the sufficiency of SOC 1 Type II reports when assessing third-party cloud environments.
- Design audit procedures to test automated controls that function without manual oversight.
- Analyze change management logs to ensure the integrity of automated financial calculations.
- Assess segregation of duties within environments where administrative and user roles frequently overlap.
- Field of study
- Audit
- Level
- Intermediate
- Prerequisites
- A basic understanding of IT General Controls and experience performing substantive testing in a standard ERP environment.
- Advance preparation
- Review the AICPA standards regarding SOC 1 reports and internal control over financial reporting for cloud-based systems.
- Delivery method
- Group Internet Based
Choose one of 2 sessions
Client Data Extraction: Getting Usable Files Out of the ERP
Covers requesting extracts that work, validating completeness against control totals, and handling difficult exports such as 90-column crosstabs.
Learning Objectives
- Identify the specific technical requirements to include in a data request to ensure exports are compatible with audit software.
- Apply validation techniques to confirm that extracted datasets align with the general ledger and control totals.
- Determine strategies for converting complex report formats, such as wide crosstabs, into flat files suitable for testing.
- Field of study
- Information Technology
- Level
- Intermediate
- Prerequisites
- Experience with basic audit data requests and a working knowledge of spreadsheet software.
- Advance preparation
- None
- Delivery method
- Group Internet Based
ITGCs for the Non-IT Auditor: Access, Change, and Cloud
Covers what to ask, what to look at, and what a SOC 1 report does and does not cover.
Learning Objectives
- Identify the three core domains of Information Technology General Controls that impact financial statement assertions.
- Evaluate the scope of a SOC 1 report to determine which user control considerations the audit team must test manually.
- Draft targeted inquiries for client IT personnel regarding logical access and change management procedures.
- Distinguish between effective ITGCs and manual workarounds when system-generated evidence is unreliable.
- Field of study
- Audit
- Level
- Intermediate
- Prerequisites
- A basic understanding of internal control concepts and experience performing financial statement audits.
- Advance preparation
- None
- Delivery method
- Group Internet Based
Choose one of 2 sessions
Verification Under Attack: Confirmations, Deepfakes, and Engagement Fraud
Covers electronic confirmation platforms, identity verification when video calls are no longer proof, and fraud patterns aimed at audit procedures.
Learning Objectives
- Identify common vulnerabilities in electronic confirmation platforms that fraudsters exploit to intercept or forge evidence.
- Recognize the technical indicators of deepfake audio and video during remote client inquiries and management interviews.
- Evaluate the effectiveness of multi-factor identity verification protocols within the context of a modern audit engagement.
- Assess how social engineering tactics have evolved to target the specific workflows of external audit teams.
- Field of study
- Audit
- Level
- Intermediate
- Prerequisites
- General familiarity with electronic confirmation platforms and remote audit evidence standards.
- Advance preparation
- Review current firm policies regarding identity verification for remote client contacts.
- Delivery method
- Group Internet Based
Securing the Audit Firm: Client Data, Portals, and Field Devices
Covers encryption, MFA and passkeys, portal hygiene, laptops at client sites, and incident response plans for lost workpaper files.
Learning Objectives
- Identify the primary security vulnerabilities associated with mobile audit devices and client-site connectivity.
- Compare the effectiveness of multi-factor authentication methods including passkeys and hardware tokens.
- Establish a protocol for client portal maintenance and user access reviews to minimize data exposure.
- Outline the essential components of an incident response plan for lost or stolen engagement files.
- Field of study
- Information Technology
- Level
- Intermediate
- Prerequisites
- A basic understanding of audit engagement workflows and common file-sharing tools.
- Advance preparation
- None
- Delivery method
- Group Internet Based
AI in the Audit File: Tools, Limits, and Evidence Standards
Covers where AI helps with document review, contract extraction, and anomaly identification, alongside standards regarding explainability, review responsibility, and relying on tool output.
Learning Objectives
- Identify specific use cases where AI tools improve the accuracy of contract extraction and document review.
- Determine the documentation requirements for AI-generated evidence to satisfy professional standards.
- Evaluate the limits of algorithmic anomaly detection when performing risk assessment procedures.
- Explain the practitioner's responsibility for reviewing and verifying the output of automated tools.
- Assess the impact of explainability requirements on the selection of audit technology.
- Field of study
- Audit
- Level
- Intermediate
- Prerequisites
- A working knowledge of current GAAS and familiarity with standard electronic workpaper documentation practices.
- Advance preparation
- None
- Delivery method
- Group Internet Based
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