SAP Concur: AI-Generated Receipts Challenge Human Audits, Verify Detection 18x Higher
SAP Concur says AI-generated receipts are evading traditional human audits because they are visually realistic and can have metadata stripped or faked. Its AI-powered auditing solution Verify has helped customers identify thousands of AI-generated receipts, with a detection rate roughly 18 times higher than earlier checks focused only on known online receipt generators. Chris Juneau, senior vice president and head of Product Marketing at SAP Concur, said about 1% of reviewed receipts have been flagged as potentially AI-generated, created by tools including ChatGPT, Gemini and Stable Diffusion, and that AI is not increasing the frequency of expense fraud but changing how it occurs. With near…
Impact and considerations
AI-generated receipts defeat manual review, can translate into meaningful losses at scale, and burden audit and accounts-payable teams, with risks to employee trust or legal exposure. Companies need to embed metadata forensics and machine-learning detection into expense workflows and tighten submission rules, such as…
Key points
- AI-generated receipts are visually realistic, mimicking logos, fonts, itemized entries, VAT lines and totals, and can have metadata such as EXIF fields, timestamps and geolocation stripped or faked, removing conventional red flags.
- SAP Concur's AI-powered auditing solution Verify has helped customers identify thousands of AI-generated receipts, with a detection rate roughly 18 times higher than earlier checks focused only on known online receipt generators.
- Chris Juneau, senior vice president and head of Product Marketing at SAP Concur, said about 1% of reviewed receipts have been flagged as potentially AI-generated, created by image generators including ChatGPT, Gemini and Stable Diffusion.
- Juneau said AI is not increasing the frequency of expense fraud but is changing how it occurs; with nearly 70% of expense transactions including an attached receipt, manual review is insufficient.
- Effective defenses pair metadata forensics with machine-learning detectors trained on large bodies of confirmed real and AI-generated receipts, kept current through continuous retraining and partner-sourced intelligence.
- Operational fallout includes overwhelmed audit teams, heavier accounts-payable workloads, undermined corporate travel program integrity, and erosion of employee trust or legal exposure from mishandled investigations.
- Finance, travel and compliance teams are adapting by tightening submission policies, making e-receipts mandatory and integrating automated tools into policy enforcement.
- A risk-based approach is recommended: automated scoring flags only higher-risk submissions for human review, supported by clear policies, transparent communication, documented decisions and easy appeals or clarifications.
Sources and time
- Primary source
- SAP Concur
- Other sources
- 0
- First source publication
- 16 Dec 2025, 21:10
- Page published
- 13 Aug 2026, 08:27
- Last updated
- 16 Dec 2025, 21:10
- Original links
- SAP Concur Blog:Fake Receipts 2.0: Why Human Audits Fail Against AI and How Tech Is Fighting Back (opens in a new tab)Primary source · en · Published 16 Dec 2025, 21:10