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The next big Subprime Mortgage Ripoff – can we spare another $15 billion?

by Avivah Litan  |  August 10, 2011  |  Comments Off on The next big Subprime Mortgage Ripoff – can we spare another $15 billion?

Home lenders and banks are losing between $7.5 billion and $15 billion in fraud from seemingly-deplorable subprime mortgage activities that get the wrong people rich quick.

It just doesn’t quit – fraud on the way into the subprime crisis, and now fraud as we try to dig our way slowly out. The techniques are essentially the same as the 2007 legacy fraud rings, except the 2007 goal was to artificially inflate the valuation and sales price, and then extract all the money with a subprime mortgage and its derivatives. This time around, the goal is to artificially reduce the valuation and sales price, while putting the mortgage into default, and then extract the money with a sale, property transfer, or even a new mortgage at the real (higher) valuation. Perhaps there was not as much incentive to stop the fraud and abusive lending practices as we got into this mess, since greed invariably got in the way – but hopefully, with the economy struggling and the market tanking again, there will be more incentive to stop the abusive foreclosure practices that are cropping up as wallets continue to shrink.

Palantir, a technology supplier that specializes in quickly integrating and making sense of all types of structured and unstructured data, has been working with the nation’s largest mortgage lenders and financial institutions on ‘solving big problems with big data management’ (for invariably big revenues that accrue to the vendor, but hey that’s the American way). In working on mortgage pricing and analysis, Palantir inadvertently stumbled across some stark and depressing facts, albeit not at all surprising. By getting its arms around data stuck in legacy green screen systems, it found that over 1% of subprime sales (where a total portfolio could amount to between $100 billion and $2 trillion) was consistently lost to fraudulent and sleazy real estate deals. Here’s how the basic scheme works:

a) Bob Borrower can’t pay his adjustable rate mortgage, now with a balance of $1 million, and the bank has serviced him with a notice of foreclosure. His home is only worth $500,000, based on sales of comparable properties in the last 90 days.

b) Bob goes searching on Google for “Foreclosure Help” and discovers the promises of Shady Foreclosure Prevention Inc. who say they can get him out of this mess if he just sends them his contact information.

c) Connor from Shady Foreclosure Prevention calls Bob the next day and tells him they can help get him out of his mess by short selling his home, whereupon Bob’s Lender (the Bank) will forgive the balance of the loan owed to them by Bob after it collects the sale price. Bob might also qualify for $3,000 to $20,000 in cash incentives from the bank or programs like HAFA.

d) Bob says OK, sounds perfect.

e) Shady Foreclosure Prevention is actually a front designed to drive foreclosed customers to a ring of realtors, appraisers, and mortgage brokers, looking to monetize distressed properties. Connor simply contacts his sister Nancy, who just got her real estate license two months ago, and tells her to ‘arrange the sale’.

f) Over the following months, Nancy only actually receives and submits low bids on behalf of non-arms-length buyers, such as her brother-in-law Joe who will say that he will be happy to buy the house, but alas he can only afford to pay $300,000.

g) Nancy tells Connor and the Bank the news that sadly enough, there was only ONE bid on the house despite their very aggressive and lengthy sales and marketing efforts.

h) The transaction between Bob and Joe goes through for $300K. Bob (or often in these distressed markets, the Bank ) pays Nancy her commission for selling his house, and Joes pays Nancy her commission fees for buying the house.

i) Nancy splits the commissions with Connor from Shady Foreclosure Prevention, per their agreement. Nancy takes Connor to dinner that night, celebrating their latest success and plotting their future ones.

j) The next day, Nancy tells Joe she thinks she can sell his house for $600,000 and Joe replies ‘Why not? Go for it.’

k) This time, it only takes Nancy 30 days to sell the house, this time to a ‘real’ buyer – a family of four. Again Nancy and Shady Foreclosure Prevention make their commissions, and split the $300,000 profit between Nancy, Connor and Joe.

And the cycle repeats. Again and again and again. Nancy and Joe enlist the help of another broker to guarantee that bank-ordered valuations support their shady deals. Eventually, Connor even defaults on his own $1 million mortgage, and sells it to an LLC for $500K, using Nancy as his realtor. The bank, investor, or government-sponsored enterprise such as Fannie Mae, end up losing 25-50 cents on every dollar loaned.

I don’t need to remind anyone how bad this is for a struggling housing market. This ends up hurting everyone – the banks, the government home lending agencies (Fannie Mae and Freddie Mac), the taxpayers and even those who earn too little to pay any taxes. It hurt’s every party’s credit ratings, empties their coffers and damages the economy. Everyone loses except the con artists.

Apparently, this con is very easy to pull off because the systems that process these sales aren’t intelligent enough to see what’s happening before their very ‘eyes’. The mortgage systems were built to pump out and service loans – not to analyze huge amounts of structured and non-structured data. (The outstanding loan value on U.S. mortgages is about $10 trillion).

But by using entity link analysis and pattern based intelligence (what we call Layer Five of Fraud Prevention – please see “The Five Layers of Fraud Prevention and using them to beat malware” ) lenders, government agencies and other entities can get their arms around disparate information, find the abuse and fraud, and stop it once and for all. This technique can work just as well in weeding out an estimated $60 billion in Medicare and Medicaid fraud annually. And it has already proven to yield significant returns in many other use cases, such as credit card bust out, insurance claim fraud and homeland security.

Instead of spending countless hours dragging our country through more uncertainty and inflamed rhetorical sessions, I personally would like to see the U.S. Congress create incentives to use Pattern Based intelligence systems to weed out billions in fraud and abuse. They could then use the savings to pay for causes that matter, such as affordable housing and easily accessed quality medical assistance for the underprivileged. Now wouldn’t that be an anomaly?

For related and more information on some sample fraud rings uncovered by law enforcement trying to pilfer almost $100 million, please see:

http://libn.com/2011/08/04/li-mortgage-firm-charged-in-58m-fraud/
http://www.themreport.com/articles/scam-artist-sting-successful-in-south-florida-2011-08-05

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Avivah Litan
VP Distinguished Analyst
19 years at Gartner
34 years IT industry

Avivah Litan is a Vice President and Distinguished Analyst in Gartner Research. Ms. Litan's areas of expertise include endpoint security, security analytics for cybersecurity and fraud, user and entity behavioral analytics, and insider threat detection. Read Full Bio




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