The robo-signing fiasco also has energized overall fraud prevention and management efforts, prompting financial service providers to focus on short sales and foreclosure fraud.
If robo-signing mistakes derived from carelessness and loan processing inefficiency fraud are even more difficult to detect and prevent, insiders agree that fraudsters who often collaborate with employees of a mortgage firm tend to challenge both lenders and their borrowers with new scams.
“Certainly the fraud is going to take the path of least resistance as it always has,” said Ed Gerding, senior fraud consultant at CoreLogic.
And as the industry focus continues to switch from originations to servicing, fraudsters did the same. What has become obvious, he said, is “a migration to the servicing side” of some of the standard origination-based fraud,” such as income and employment misrepresentation.
According to Gerding, one unintended consequence of major federal foreclosure assistance programs such as the Home Affordable Modification Program (HAMP) and the Home Affordable Refinancing Program (HARP) is that they created “a lot of opportunities” for fraudsters.
If before HAMP and HARP borrowers might have been tempted and did state egregious incomes that they did not make, as federal assistance became available, they are now trying to understate their income “in an effort to get a better modification outlook or better modification decision on the servicing side of the house.”
The ongoing increase in delinquencies and foreclosures has created a breeding ground for foreclosure rescue scams to continue, he says.
“It's just one of those things where the pendulum from a risk-management perspective has swung to the risk-averse side," Gerding said. "Now it's just a matter of trying to get the controls and fraud prevention and detection tools in place before that herd starts moving in the direction of production again.”
One popular servicing fraud scam is when the fraudster targets a bank-owned property, replaces the old lock with a new one, and then rents the place. Often these fraudsters require a security deposit for the first and the last month, which can translate into a check of up to $6,000 or more — before the fraudster disappears.
In such cases, both the bank and renter are deceived since it may take time for the bank to realize there are squatters in the house, while the renter is not even aware of being part of an illegitimate deal.
Joe Filoseta, president and CEO of DepotPoint, said another “even better” scam similar in structure is where the lockbox and sign are taken off and the fraudster uses Craigslist to make several appointments at different times of the day, then takes security deposits and signs leases with seven or eight people on one single property. As a result, these fraudsters can make up to $20,000 or $30,000 on a single property, “particularly the high-end ones.”
The industry is responding to these fraud scams with better tools that could be used to screen fraudsters once these individuals and their tactics are identified. In addition, servicers are better prepared in the operational side because of HAMP and now HAFA and all the challenges of the past several years.
Gerding said that while that is “incrementally happening” as some of the largest servicing operations have increased their default staff to 15,000 from 1,200 and have opened several servicing centers, “where do you find 12,000 to 13,000 qualified people to do default servicing?…Where do you find people with short-sale expertise? You don’t.”
Gerding agreed with other industry insiders who find that part of the reason why there is such shortage of expertise is the fact that until a few years ago short sales where not on anyone’s agenda.
So now the only alternative for the industry is to react the same way it responded to the need for automated underwriting, “broadly apply technology to the process,” he said, come up with a time-based, workflow-controlled expert system “where the amount of expertise that’s required by an individual is replaced by the guidance of the technology.”
Automated underwriting took advantage of “the very best expertise,” he argued, which was embodied into the systems, whether they were rule-based, network-based, or case-based. “The issue is, we normalized data, we made it transparent, we submitted it to a decision server and we all believed it was a good decision.”
