Not long ago, a large Midwestern community bank was faced with a lending nightmare – a borrower had taken out a business loan of millions of dollars and suddenly stopped paying. To locate the missing borrower, they hired Cendrowski Corporate Advisors, a firm that works with attorneys and legal teams to specialize in forensic accounting and fraud investigation services. Using Thomson Reuters CLEAR online investigative software, investigator Theresa Mack uncovered the truth – that the borrower was someone far different from whom he'd presented himself to be.
Mack started with what the bank had: the borrower's name, payment records, Social Security number and contact information. "I wanted to understand who this individual was," she said. Before making the loan, the bank had used a third-party firm to verify that the borrower's SSN was valid.
Using CLEAR, she entered this information and pulled all addresses associated with the data. The dashboard tool gave her ranked and rated results, quickly assembling a comprehensive, easy-to-understand picture of the borrower. One address in these results caught her attention. "It was an address that belonged to a name that was similar to this person's, but who had a different Social Security number," she said.
Running this new name on CLEAR, Mack discovered the person "had a whole identity." And while the new person had a different SSN from the borrower, and his name was slightly different, there were telling similarities between the two identities. For example, their date of birth was the same, as was their spouse's name.
Mack sketched out the two individuals – the bank's missing borrower ("Person A") and "Person B," the person with similar biographical details. For the latter, she used CLEAR to "pull all the property that he owned."
She was able to run separate CLEAR searches for both individuals and compare the two. Viewed side by side, each man had a similar story: someone who amassed large debts from a number of banks, purchased commercial properties, collected rent from tenants, then defaulted on his loan obligations. Person B had "amassed all of these loans, purchased all of this commercial property, and then had filed for bankruptcy."
After pulling Person B's bankruptcy records, Mack contacted the bankruptcy trustee who had handled the case. He remembered the person and provided more details. This conversation convinced Mack that Person A and Person B "were one and the same person because of the similarities. The date of birth matched, the name of the spouse matched."
However, she might not have discovered the borrower's alternate identity except for the old address that she found via CLEAR. "That's what linked it, that one address – he slipped up."
Using CLEAR to solve the case
During her time with the Federal Bureau of Investigation (she's now retired from the Bureau), Mack often used CLEAR in her investigative work. It's still the first thing that she uses when starting a new case. There's usually a clock ticking when she's trying to track down an individual or solve a case. That's why it's reassuring to know that CLEAR will "provide deep information, relevant information. It gives you what you need to know."
Her investigative strategy is to focus on addresses first. "I'll search all the addresses, to see what businesses are connected to them, what people are connected," she said. "By searching for addresses only, and not putting any person's name in there, I can pull up businesses or any individuals that are tied to any address. Sometimes these are people who don't show up on the first search if you search by name."
In this bank fraud case, Mack said CLEAR "provided me with the necessary link that steered me to the true person, to his true identity."
Making the case for fraud
As it turns out, the reason why the borrower wasn't responding to the bank, why he wasn't coming into court, was because in questioning "he doesn't want to say under oath that he's so-and-so, when he is actually the first person," Mack said.
She was surprised that the due diligence firm the bank had used hadn't seen any red flags when verifying the borrower's identity due to CIP protocols. Then she learned they were a third-party firm that only charged $100 for identity verification. "And I told [the bank], well, $100 gets you nothing. You just verified his Social Security number with his name." The bank has since upgraded its due diligence efforts.
When the fraudulent borrower had filed for bankruptcy 15 years ago and had assumed a new identity, it was easier to pull off his scheme. In the past, Social Security didn't regularly communicate with credit bureaus, which made SSN fraud harder to detect. "Not long ago, you could make up a Social Security number, put it on the shelf and backstop it – maybe get a credit card with it," Mack said. "Just make it look like it's real and keep it dormant until you need it. That's what I think he did here."
Resolving the case
Armed with Mack's information, the bank went to court to claim they'd been defrauded by a borrower using a false identity and false Social Security information. It turns out that at least 10 other banks had lent to the same borrower. By getting into court first, the community bank was "able to get a judgment against him, and collect," Mack said. "It's first-come, first-served, as far as collecting goes. At least they were able to collect some funds from this situation."
After she'd completed her report, she told the bank they should notify the Social Security Office of the Inspector General. "Someone needs to know he's using two numbers, and he could further defraud the system by collecting Social Security off both numbers." The bank asked her to pursue the matter. She provided the Social Security OIG with the details, and they've since opened a fraud case.
It's unclear whether the fraudulent borrower's other lenders will be as successful in their quest for restitution. Luckily for the community bank, they hired an investigator with extensive experience and who, by using CLEAR, could thoroughly assess even the most seemingly unassuming leads.
Thomson Reuters is not a consumer reporting agency and none of its services or the data contained therein constitute a ‘consumer report’ as such term is defined in the Federal Fair Credit Reporting Act (FCRA), 15 U.S.C. sec. 1681 et seq. The data provided to you may not be used as a factor in consumer debt collection decisioning, establishing a consumer’s eligibility for credit, insurance, employment, government benefits, or housing, or for any other purpose authorized under the FCRA. By accessing one of our services, you agree not to use the service or data for any purpose authorized under the FCRA or in relation to taking an adverse action relating to a consumer application.