Expense fraud remains a persistent challenge for finance teams, often hiding in plain sight across thousands of transactions. We’ve gathered insights from AppZen expense management experts on the evolving nature of expense fraud and how AI technology is changing the detection landscape.
The hidden world of expense fraud
Detecting fraud isn’t simply about finding the obvious violations. It’s about uncovering patterns that reveal dishonest behavior over time. As one finance leader noted: “Everything can be explained away if you’re looking at it one time, but when I see it five times in a row, that explanation doesn’t really count anymore.”
The most common expense fraud techniques are surprisingly simple. Here are the top ways employees hide expenses.
Missing receipt affidavits - Employees claim they lost receipts to disguise personal purchases or entertainment as business expenses
Non-itemized receipts - Submitting total-only receipts that hide details (e.g., alcohol purchases or personal items at hotels)
Staying just under limits - Consistently spending just below policy thresholds (e.g., $24.99 meals when limit is $25)
Relying on MCC codes - Merchant codes can be misleading (e.g., strip club purchases appearing as “bar” expenses)
The challenge for many organizations is that these behaviors aren’t obvious when examining individual, isolated transactions.
The limitations of traditional approaches
Manual auditing creates several obstacles to effective fraud detection:
Resource constraints – Teams can typically only review a small percentage of total expenses
Contextual challenges – Basic OCR technology can’t distinguish between “margarita pizza” and an alcoholic “margarita”
Inflexible rule systems – Template-based solutions fail when receipt formats change
Inconsistent enforcement – Manual reviews apply policies differently across transactions
These limitations create environments where fraud can flourish. In one extreme case we’re familiar with, an IT department head sent Venmo payments to his brother, fraudulently claiming legitimate consulting work. The resulting loss was $360,000 that went undetected through manual processes.
Customer Success Story: T.D. Williamson
A real-world example from one of our customers highlights how AI can transform expense management processes. T.D. Williamson, a company processing approximately 9,000 expense reports annually, struggled with a manual audit approach before implementing AI solutions.
Before AI implementation
- Inconsistent enforcement of expense policies across different managers and departments
- Significant delays in employee reimbursement due to manual review bottlenecks
- What one finance leader described as “arts and crafts” Excel reporting that provided limited visibility
- No standardized way to identify behavioral patterns across thousands of transactions
After AI implementation
- 100% of expense reports evaluated against consistent policy standards
- Dramatic improvement in reimbursement timing while maintaining control
- Comprehensive reporting that revealed previously hidden spending patterns
- Ability to identify and address policy violations systematically rather than randomly
This transformation allowed T.D. Williamson to maintain proper oversight while reducing the administrative burden on its finance team. Most importantly, it shifted the company’s approach from reactive spot-checking to proactive pattern detection.
The value of AI in fraud detection
AI-powered expense auditing addresses these challenges by enabling organizations to:
- Review 100% of expenses before payment
- Scale audit capabilities without adding headcount
- Reduce processing time by up to 80%
- Apply risk scoring to prioritize suspicious transactions
- Enforce policies consistently across all submissions
Finance AI technology pays particular attention to patterns that develop over time, like weekend spending without a business justification, regular submissions just under threshold limits, or repeated use of missing receipt affidavits.
“One area that nobody should neglect is, at minimum, the duplicate check,” noted Saman Khatami, Customer Success Manager at AppZen. “Duplicate checks identify when someone is paid twice for the same expense. If they go to lunch, spend 10 bucks, and submit it twice for $20, they’re making extra money on a one-time charge. There’s no justification for that whatsoever.”
Best practices for fraud prevention
Based on our extensive experience helping companies overcome these challenges, we recommend several approaches to strengthen expense fraud prevention:
Look for patterns rather than incidents. Review spending behavior over time to identify suspicious trends that single transactions might miss.
Implement clear and consistent enforcement. Ensure policies are regularly updated and apply the same standards to everyone.
Focus attention on high-risk areas. Use AI to highlight the outliers and unusual transactions for manual review.
Review performance regularly. Quarterly assessments of audit effectiveness help identify improvement opportunities.
Use data for education. Share insights with employees to clarify policy expectations and reduce unintentional violations.
Moving beyond transaction-level analysis
Perhaps the most valuable insight we’ve gained over the years is the importance of shifting from transaction-level to pattern-level analysis. As one customer shared with us: “We want to refocus on behavior over time because we’re so transactional. We’re looking at it at one instance at a time.”
This perspective change transforms expense management from a clerical function to a strategic one, supporting better policy design, improving expense culture, and protecting company resources. Modern AI solutions like AppZen Expense Audit don’t just find individual violations, they uncover the patterns that reveal systematic abuse. For finance teams looking to prevent expense fraud, this shift from transaction analysis to behavior analysis using AI represents the future of effective expense management.
