Automating Expense Reimbursement Audits: A Step-by-Step Guide

Expense reimbursement audits are a perfect starting point for AI automation. They’re high-volume, rule-based, and traditionally time-consuming. With the right approach, you can move from sampling 50 expense reports to testing your entire population—in less time than the manual sample took.

Here’s how to automate expense audits step by step.

Why Expense Audits Are Ideal for Automation

Before diving into the how, let’s understand why expense audits are such a strong automation candidate:

Clear policy rules: Most expense policies have explicit thresholds (meals under $75, mileage at $0.67/mile, approval requirements by amount)
Structured data: Expense management systems export clean, consistent data fields
High transaction volumes: Testing 10,000 expenses manually is impractical; AI handles it effortlessly
Low ambiguity: Policy violations are usually binary—the receipt exists or it doesn’t

Step 1: Define Your Testing Criteria

Start by translating your expense policy into testable rules. Common criteria include:

Amount Thresholds

Meals exceeding per diem limits
Travel expenses above approval thresholds
Entertainment expenses requiring additional authorization

Documentation Requirements

Missing receipts for expenses over $25
Incomplete expense descriptions
Missing business purpose documentation

Approval Workflows

Expenses approved by the submitter themselves
Approvals outside the submitter’s chain of command
Expenses submitted after policy deadlines

Duplicate Detection

Same amount, same vendor, same date across submissions
Receipts reused across multiple expense reports
Split transactions to avoid approval thresholds

Pro tip: Prioritize rules that have caught the most exceptions historically. Start with your top 5-10 criteria and expand from there.

Step 2: Prepare Your Data

Clean data is essential for accurate automation. Work with your expense system administrator to export:

Transaction details: Date, amount, category, vendor, description
Approval data: Approver name, approval date, approval hierarchy
Receipt metadata: Attached files, receipt dates, amounts
Employee data: Department, manager, spending limits

Ensure data fields are consistently formatted. AI can handle variations, but standardized data produces more reliable results.

Step 3: Configure Your AI Testing Agents

With Torvia’s expense audit agent, you configure your criteria once and reuse them across audit periods:

Threshold Tests

Map your policy limits directly into the testing configuration. The AI will flag every transaction exceeding your defined thresholds, not just a sample.

Pattern Detection

Beyond explicit rules, AI excels at identifying patterns that suggest policy circumvention:

Expenses consistently just under approval thresholds
Unusual submission timing (month-end bunching)
Vendor spending concentration

Cross-Reference Validation

Connect expense data to supporting systems:

Match expense dates to calendar entries for travel verification
Cross-reference vendors against approved supplier lists
Validate mileage claims against mapped routes

Step 4: Run Your First Automated Test

Choose a recent, closed expense period and run your automation in Review Mode. This lets you:

See every exception the AI identifies
Validate the AI’s reasoning before finalizing
Adjust thresholds if they’re too sensitive or too permissive
Build confidence in the automated approach

Review a sample of the exceptions and non-exceptions. Confirm the AI is interpreting your rules correctly.

Step 5: Refine and Expand

Based on your first run, you’ll likely find opportunities to improve:

False positives: Legitimate expenses flagged as exceptions may indicate rules that need refinement
Missing criteria: Patterns you notice that weren’t captured in your original rules
Data quality issues: Fields that need cleanup in the source system

Iterate until your exception report represents true policy violations worth investigating.

Step 6: Document and Operationalize

Once validated, create your standard expense audit workpaper template:

Scope: Full population of expense transactions for the period
Criteria: Link to your configured testing rules
Results: Exception counts, categories, and materiality
AI trail: Complete log of AI reasoning for each exception determination
Conclusions: Your professional assessment of the control environment

This documentation satisfies external auditor requirements and provides transparency into your AI-assisted methodology.

Expected Results

Organizations automating expense audits typically see:

100% population coverage instead of 1-5% sampling
80% reduction in testing time for the audit team
Higher exception detection due to comprehensive testing
Consistent application of policy rules across all transactions

Common Pitfalls to Avoid

Over-automation too soon: Start with clear, unambiguous rules before tackling gray areas
Ignoring false positives: High false positive rates erode trust in the automation
Skipping validation: Always verify AI results against known outcomes initially
Neglecting the audit trail: Ensure AI reasoning is captured for workpaper documentation

What’s Next

Once expense audit automation is running smoothly, you’re ready to apply the same approach to other high-volume, rule-based areas:

Payroll Audit Automation — Detect anomalies in your payroll population
Access Control Audits — Automate user access reviews at scale

Ready to automate your expense audits? Request a demo and see full population testing in action.