At a Glance
- A Secured Research survey of 187 equipment finance credit leaders found that 38% of confirmed origination fraud cases in the trailing 12 months involved applicant profiles that had passed manual credit review at least twice.
- Fraud losses per funded deal have grown 3.4 times faster than portfolio assets across the respondent set, and most operations cannot distinguish fraud loss from general credit loss in their current reporting.
- Synthetic identity, equipment misrepresentation, and straw-borrower schemes dominate the loss data. Each requires a different detection pattern, and none are reliably caught by conventional underwriting review.
- The next generation of fraud detection augments the underwriter rather than replacing judgment — it flags the deals that human pattern recognition is structurally unable to see.
The Loss Category You Haven’t Quantified
A chief credit officer at a non-bank independent recently asked his portfolio analytics team a simple question: what share of charge-offs in the trailing 24 months were driven by fraud rather than general credit deterioration? The team worked on the answer for six weeks and came back with a range rather than a number. Their upper bound was almost three times the firm’s internal assumption.
This is not a firm-specific problem. Most equipment finance operations charge-off fraud losses through the same general ledger accounts they use for credit losses because the work required to separate them is painful and the business rationale to do so has historically been weak. The result is a widespread, structural underreporting of a loss category that has grown faster than any other in the portfolio. Senior risk leaders who have done the reconstruction work universally describe the exercise as uncomfortable and universally report that the magnitude justified it.
