Top Five Credit Application Fraud Flags

Long ago and far away, I worked on the finance side of our business. One of my responsibilities was to manage the company’s risk against dealer fraud. I developed a tool I named the Credit App Fraud Red Flags Report to help in this effort.
The report was generated from every submitted credit application, whether we bought the deal or not. It tracked a number of potential red flags we had identified in reviewing defaulted deals as potential indicators of dealership fraud.
I am not asserting that any of the following examples are absolute indications of credit app fraud, just red flags worth further investigation:
1. Plus One
When I review credit applications in deal files, I focus on the five key determinants that comprise the customer’s stability and capacity components in a decisioning algorithm. I occasionally come across credit apps that disclose time on the job and time at the residence as “X years, 1 month.”
Antiquated scoring algorithms assigned points to time on the job and at the address. The more points, the better the buy rate and likelihood of approval. Adding that extra month was a way to circumvent the scoring algorithm.
2. Employer Name and Address
I once found in a compliance review that every customer was a “manager.” When I asked the dealership’s general manager about it, he said with a straight face that everyone “manages” something in life.
Managers are the occupation-fraud catchall. A restaurant server is promoted. A business owner is demoted.
Telltale signs that the customer is self-employed include his or her own name appearing in the business name or matching home and business addresses.
Finance sources and the Federales consider reporting self-employed customers as managers of their businesses potential bank fraud. Do not attempt to circumvent underwriting guidelines to avoid additional stips, such as bank statements or tax returns.
3. High Income, Low Rent
Mortgage lenders generally recommend that an applicant’s monthly mortgage payment not exceed 28% of gross monthly income. I used this metric to flag deals with a housing expense of less than 15% of gross monthly income.
Of course, there are many cases in which the housing expense is correct at a lower number. There are also instances when the dealership manager has a habit of under-reporting the next red flag on our list.
4. Housing Expense
Let me start by setting expectations: The Federales expect you to report the amount the customer is contractually obligated to pay for housing. I find four different types of manipulated housing expense on credit apps:
- A mortgage split between spouses, partners or roommates.
- Some finance sources internally apply a minimum housing expense on every credit application for debt ratio calculations. I’ve seen some managers use that minimum as the standard rent regardless of reality.
- Some finance sources look to see if the dealer’s inquiry is on the credit bureau report before the credit application was submitted. The finance source compares any reported housing expense to the data supplied by the dealer. If the dealer-supplied expense is lower, red flags wave.
- Decades ago, some trainers got cute and taught that if someone is living with a spouse or a partner, that meant that person was “living with relatives” — even if the customer had a mortgage or lease.
5. Other Income
Dealership managers should accurately disclose all legitimate income to the finance sources. When I see additional income on multiple credit applications sourced by the same manager, I suspect they have been manipulated. The source of the other income is usually listed simply as “Other,” a bad sign.
If the deal would otherwise qualify, we would fund the deal and add a note to the account. The note would say that in the event of a default there might be cause to have the dealer buy back the deal.
As a second dealership risk, if the finance source can confirm the data was manipulated, it is required to file a suspicious-activity report with its regulator.
Continued good health, good luck and good selling.