Stern’s Foreclosure Mill Lays Off 300 People

Did you know that the Wall Street money pumped into David Stern’s Law Office resulted in a public company that is actively traded? Well, it is. And it isn’t doing too well lately.

Stern’s DJSP announces 300 layoffs

South Florida Business Journal – by Paul Brinkmann
Date: Monday, October 25, 2010, 10:45am EDT

Fallout from the national foreclosure crisis continues to impact companies associated with foreclosure attorney David Stern – one of the leading foreclosure attorneys in the nation.

His law firm has filed tens of thousands of cases on behalf of lenders and mortgage agencies such as Fannie Mae. The firm has been under investigation by Attorney General Bill McCollum for allegedly creating false documents in foreclosure cases.

Here’s the latest: The company that conducts support work for Stern’s law firm, Plantation-based DJSP Enterprises (NASDAQ: DJSP), now admits to about 300 layoffs since “recent developments” began.

I first reported that Stern’s law firm and affiliated companies were laying off hundreds of people on Oct. 12. At that time, Stern’s attorney, Jeffrey Tew, said there were fewer than 100 layoffs from the law firm, and they were temporary positions.

Another departure from DJSP’s board of directors was announced Monday – that of Mark P. Harmon, a Boston-based foreclosure attorney. We reported on the Oct. 19 departure of several officers and that Stern had relinquished the chairmanship of the board.

DJSP’s stock slipped briefly below the crucial $1 mark last week. The stock was up 7 cents, to $1.11, in Monday morning trading. NASDAQ’s policy allows it to delist stocks that fall below the $1 mark for 30 days.

Stern’s law firm has struggled with declining case volume since major lenders started putting a hold on foreclosure action in September, according to DJSP’s news release about the layoffs. Mortgage giants Fannie Mae, Freddie Mac and Bank of America have stopped sending cases to Stern’s firm. The public company, DJSP, is dependent on paperwork processing from Stern’s law firm.

The law firm has defended itself in court against McCollum’s subpoena, calling his investigation overly broad and illegal. But, a Broward County judge has ruled in favor of the subpoena.

In broader related news, The Wall Street Journal reported Monday that Bank of America acknowledged some minor mistakes in foreclosure files as it begins to resubmit documents in 102,000 cases. The paper also reported on its website that Federal Reserve Chairman Ben Bernanke said the agency was “seeking to determine whether systematic weaknesses are leading to improper foreclosures.”

14 Responses

  1. DJSP stock falling fast… will be de-listed shortly just like their benefactor Fannie Mae, aka the American Taxpayer… this guy is a flight risk and should arrested before sundown!

  2. […] This post was mentioned on Twitter by John Carmine, i8 wamu and kim thomas, Financial Wellness. Financial Wellness said: Did you know that the Wall Street money pumped into David Stern’s Law Office resulted in a public company that is … […]

  3. Stern’s future cell mate will say,

    “Your ass is my ass.”

  4. Then read this

    My Manhattan Project
    How I helped build the bomb that blew up Wall Street.
    By Michael Osinski
    March 29, 2009
    I have been called the devil by strangers and “the Facilitator” by friends. It’s not uncommon for people, when I tell them what I used to do, to ask if I feel guilty. I do, somewhat, and it nags at me. When I put it out of mind, it inevitably resurfaces, like a shipwreck at low tide. It’s been eight years since I compiled a program, but the last one lived on, becoming the industry standard that seeded itself into every investment bank in the world.
    I wrote the software that turned mortgages into bonds.
    Because of the news, you probably know more about this than you ever wanted to. The packaging of heterogeneous home mortgages into uniform securities that can be accurately priced and exchanged has been singled out by many critics as one of the root causes of the mess we’re in. I don’t completely disagree. But in my view, and of course I’m inescapably biased, there’s nothing inherently flawed about securitization. Done correctly and conservatively, it increases the efficiency with which banks can loan money and tailor risks to the needs of investors. Once upon a time, this seemed like a very good idea, and it might well again, provided banks don’t resume writing mortgages to people who can’t afford them. Here’s one thing that’s definitely true: The software proved to be more sophisticated than the people who used it, and that has caused the whole world a lot of problems.
    The first collateralized mortgage obligation, or CMO, was created in 1983 by First Boston and Salomon Brothers, but it would be years before computer technology advanced sufficiently to allow the practice to become widespread. Massive databases were required to track every mortgage in the country. You needed models to create the intricate network of bonds based on the homeowners’ payments, models to predict prepayment rates, and models to predict defaults. You needed the Internet to sail these bonds back and forth across the world, massaging their content to fit an investor’s needs at a moment’s notice. Add to all this the complacency, greed, entitlement, and callous stupidity that characterized banks in post-2001 America, and you have a recipe for disaster.
    I started on Wall Street on October 5, 1985. I was 30 years old and had been writing software for six years. I originally got into it when my wife became ill and I took a job entering data, the bottom of the computer industry, at Emory University, so her rare kidney ailment could be treated. Before that, I had risked my life for $200 a week hauling shrimp 100 miles offshore from Cape Canaveral, and I had been the only white boy in my crew digging ditches in Alabama. Compared to all that, Wall Street was a country club. I recall my first day at Salomon Brothers, lingering at the windows by the elevator banks on the 25th floor of 55 Water Street. While groups of the well dressed and the professionally coiffed headed to their cubicles and offices, I stared out at the harbor, watching freighters, tankers, ferries, and garbage scows cross the great harbor. The perfection of the place was profound, the feng shui was palpable. As John Gutfreund, then the CEO, expected, I was ready to grab the balls of the bear.
    My first assignment was to write a “machine-to-machine interrupt handler.” That was not exactly sexy in the world of finance, or in any world, and I won’t bore you by trying to explain. It was plumbing. As was all the programming, which, on the firm’s hierarchy, ranked somewhere above the secretarial pool but well below, literally and figuratively, the trading floor. I didn’t mind. To me, it was good, well-paying work. My manager, a former mathematics professor named Leszek Gesiak, an immigrant from Poland, became a friend. Neither one of us was on track, but we both enjoyed the challenges and pace of the job. We lunched at either Yip’s, a Chinese culinary cul-de-sac, or on Front Street, in the seaport, where you could get fresh fish cafeteria style across the street from the market. It was a different New York, still picking itself up from the seventies. Drug dealers loitered at the door of the brokerages, and taxis often smelled of pot from their previous occupants. Just a few years before, Michael Bloomberg had been fired from Salomon. He had the crazy idea that the data was as valuable as the firm’s capital.
    When I asked Leszek what the busy group did that sat next to us, he told me they created mortgage-backed securities. It was an instrument, he claimed, designed to keep programmers employed. Having started to overcome my aversion to the overpaid life—I had recently bought a suit at Barneys, the old one on Seventh Avenue—I asked him how the bonds worked.
    “You put chicken into the grinder”—he laughed with that infectious Wall Street black humor—“and out comes sirloin.”
    I wanted a piece of that. But first, I kept a promise to my wife—that if she recovered, we would backpack around the world.
    Returning to New York a year later, I had an interview at Shearson Lehman’s mortgage-research department. Again, I sought advice from Professor Gesiak. I drove to his apartment in Greenpoint and confessed to him that I had never studied finance, and I had only taken one course in computers. Over the kitchen table, while his wife minded the toddlers, he gave me a quick tutorial on the “present value of future cash flows.” It was only freshman calculus, after all.
    Out the back window, clotheslines on pulleys ran across the courtyard to adjoining apartments, like a scene from The Honeymooners. Once I demonstrated that I understood how to discount a cash flow, Leszek brought out the hard stuff. Over glasses of vodka chased by raw garlic and butter on rye, he recounted how he had black-marketed goods in communist Poland. Halfway through the bottle, he claimed that the Polish zloty had been on the vodka standard—that is, the conversion ratio of zlotys to dollars on the black market was always the same as the price, in zlotys, of a half-liter of vodka.
    Heading back to Manhattan that night, I smashed my car on the ramp up to the BQE. But the good news was that I got the job. I was in the mortgage-packaging business.
    At Lehman, I began a thirteen-year effort to streamline the process of securitizing home mortgages, as well as other forms of debt. That was 1988, around the time of the savings-and-loan crisis. Remember that one? Lenders had gone nuts with, what else, real estate, and as they went bust, the government was stepping into the breach. Mortgage securitization was the answer. Retail lenders could make the loan, take a fee, then sell the mortgage to an investment bank. The bank, after bundling thousands of the mortgages together, could, through a little software magic, issue bonds based on that bundle of loans. Now, an investor does not want a single person’s mortgage, much the same as you may not want to underwrite your sibling’s purchase of an overpriced McMansion. But when 1,000 similar loans are combined, and the U.S. government, through Freddie Mac and Fannie Mae, absorbs the default risk, you now have a nifty little AAA-rated piece of paper paying one or two points above Treasury bills. And if the value of the loans is in excess of the limit set by the government agencies, your savvy friends on Wall Street can create a class of subordinated bonds that will absorb all the defaults in the deal. With friends like these …
    While I slaved away at the sausage grinder, CMOs took off—$6 billion were issued in 1983, and by 1988, the annual output had jumped to $94 billion. This was the era described in Liar’s Poker. Wall Street guys felt cool and funny; people who were getting ripped off were dumb and ugly and deserved it. I got a $50,000 bonus check, a 50 percent dollop on top of my salary. Peanuts to the traders, but a bloody fortune to me, for the easiest work I’d ever done. I could afford to rent a nicer place in Greenwich Village, go out to jazz clubs, bike in France. But even then, I was wondering why I was making more than anyone in my family, maybe as much as all my siblings combined. Hey, I had higher SAT scores. I could do all the arithmetic in my head. I was very good at programming a computer. And that computer, with my software, touched billions of dollars of the firm’s money. Every week. That justified it. When you’re close to the money, you get the first cut. Oyster farmers eat lots of oysters, don’t they?
    I never would have thought, in my most extreme paranoid fantasies, that my software, and the others like it, would have enabled Wall Street to decimate the investments of everyone in my family. Not even the most jaded observer saw that coming. I can’t deny that it allowed a privileged few to exploit the unsuspecting many. But catastrophe, depression, busted banks, forced auctions of entire tracts of houses? The fact that my software, over which I would labor for a decade, facilitated these events is numbing. Is capitalism inherently corrupt? I don’t think the free flow of goods in and of itself is the culprit. No, it’s the complexity masked by thousands of unseen whirring widgets that beguiles people into a sense of power, a feeling of dominion over the future.
    As demand for mortgage bonds rose, mortgage rates went down. This was the late eighties. Through CMOs, the sheikhs whom we paid to fill up our SUVs could finance our mortgages, the core of the American Dream, as could the Chinese government—all the while getting an extra point or two above the Treasury. Ample financing allowed more people to buy their own homes. The world came full circle. Bonuses got bigger because the Wall Street boys were doing good for themselves and the world.
    As CMOs became more complicated, my job was to make everything seem simple—to, in effect, mask the complexity that would’ve made the bonds difficult to trade. We invented a language for mortgage-backed bonds. I called it BondTalk. Lehman was a runner-up in CMO underwriting. I was told to rewrite the entire system. Make it all push-button. Flexible and faster. Traders told us what they wanted, and we wrote the software code to make it possible. We were on the cutting edge. When I finished that project, I approached my former boss to ask if I could move to the trading desk, to where the big money was.
    “Mike,” he told me when denying my request, “can you really look for people dumber than you and then take advantage of them? That’s what trading is all about.”
    Yes, I assured him, yes, yes. But no deal. The next month, after I pocketed my $100,000 bonus, I left Lehman for Kidder, Peabody, which was the No. 1 underwriter of CMOs but had outdated software.
    Working with another programmer, I wrote a new mortgage-backed system that enabled investors to choose the specific combinations of yield and risk that they wanted by slicing and dicing bonds to create new bonds. It was endlessly versatile and flexible. It was the proverbial money tree.
    Another recession began, which, in the perverse world of the bond market, was good for business. As the government lowered interest rates to stimulate the economy, bonds increased in price. With a drop in rates, more people refinanced. There was more product for the securitization process, more meat for the grinder. Our software was rolled out to ride the latest wave. Traders loved it. What had taken days before now took minutes. They could design bonds out of bonds, to provide the precise rate of return that an investor wanted. I used to go to the trading floor and watch my software in use amid the sea of screens. A programmer doesn’t admire his creation so much for what it does but for how it does it. This stuff was beautiful and elegant.
    The aim of software is, in a sense, to create an alternative reality. After all, when you use your cell phone, you simply want to push the fewest buttons possible and call, text, purchase, listen, download, e-mail, or browse. The power we all hold in our hands is shocking, yet it’s controlled by a few swipes of a finger. The drive to simplify the user’s contact with the machine has an inherent side effect of disguising the complexity of a given task. Over time, the users of any software are inured to the intricate nature of what they are doing. Also, as the software does more of the “thinking,” the user does less.
    I made $125,000 in my bonus that year and bought an apartment on Gramercy Park. I had first-tier seats to the ballet, but I still rode my bike to work. The traders pocketed multiple millions. I wasn’t poor, but I wasn’t a plutocrat. I could live with myself. If there was a deception going on, I was but a small cog, I thought.
    The world around me, though, had become bizarre. At the time, I had an odd sensation that mortgage traders felt they had to outdo the loutish behavior in Liar’s Poker. The more money they made, the more juvenile they became. What do you expect from 30-year-old megamillionaires whose overwhelming aspiration was something vaguely called Hugeness? They had wrestling matches on the floor. Food-eating contests. Like little kids, they scrambled to hide the evidence when the head of fixed income paid his rare visits to the floor.
    Now that I was spending more time on the floor, I wondered why the men’s room always stank. Then one afternoon at three, when I was in there taking a leak, I discovered the hideous truth. Traders had a contest. Coming in at eight, they never left their desks all day, eating and drinking while working. Then, at three o’clock, they marched into the men’s room and stood at the wall opposite the urinals. Dropping their pants, they bet $100 on who could train his stream the longest on the urinals across the lavatory. As their hydraulic pressure waned, the three traders waddled, pants at their ankles, across the floor, desperately trying to keep their pee on target. This is what $2 million of bonus can do to grown men.

    The economy improved. The Feds raised rates. Kidder was in trouble. We had no risk management. According to an internal report, there were management deficiencies across the board. If I remember correctly, one top executive had a contract stipulating that he would only work one day a week for his seven-figure wage. So Kidder was in bad shape when it was hit by the scandal involving the infamous Joseph Jett, who allegedly fabricated hundreds of millions of dollars in trades, more or less taking down the whole firm. Back then, a major Wall Street failure didn’t panic the entire country. Kidder may have handled a fifth of the country’s mortgage-backed securities, but in the wake of its demise, the American economy did not wither. Though securitization slowed to a crawl, breadlines weren’t forming. Homeowners made their payments. Bonuses, if you got one, were halved. People stood pat. Paine Webber cherry-picked traders and programmers. G.E. sold the assets of the firm. One of those assets, to my great surprise, was my software, purchased by Intex Solutions in Boston.
    During the transition, I used the time to extend our structuring model to subordinated bonds. Allow me to expand Professor Gesiak’s analogy a bit: For deals with non-agency loans—that is, not Freddie or Fannie—in addition to the sirloin that comes out of the grinder, there is a small percentage of offal. By running that offal through the grinder again, in effect bundling together all the pieces from various deals that absorbed the default risk, we then created some Andouille and some real dog food. The rise in price of the sausage over the offal more than compensated for the unsalable leftovers. That junk typically couldn’t be sold and stayed in-house, eventually becoming known as a “toxic asset.”
    Times were lean at Paine Webber. The mortgage market, notoriously illiquid in bad times, petered out. Mortgage refinancing’s dwindled. The supply of raw material, new mortgages, disappeared. We had to lay off half of research. After a day of bloodletting, one of the bosses cornered me in the hallway. Did I get a sexual thrill out of firing people, he wanted to know, because it had always worked for him, big time.
    That was 1995. I had been on Wall Street for ten years. I was fed up with the life, all day staring at a screen, the jockeying for bonuses. I wanted something different. I biked up to Boston and proposed to the people who had bought the Kidder software that I run it for them. “Don’t pay me a cent,” I told them. “I’ll integrate with your existing software, market it, maintain it, and enhance it. We’ll split the money, if any comes in, 50-50.”
    They sent me a five-year contract with a subsequent five-year noncompete. That noncompete would retire me if enforced. I stared at it. Another five years was all I could take. Without consulting my lawyer, I signed it. Those pen strokes effectively capped my Wall Street career. Now it was up to me to chop some wood.
    We had a deal. Intex was the largest supplier of cash flows on existing CMOs, but the company could not create new structures. That’s why Intex had bought my software from G.E. But it could not get it to run, much less sell it. I spent six months in my apartment, over the phone with one of the Intex programmers, integrating the two softwares. Within a year, we had sold it to four large investment banks; by the end of 1997, we had fifteen. We were it! By the end of ’98, we had 25. If a firm wanted to be in the mortgage business, they needed us. Instead of hiring a large staff to write the software, you could buy it from us, at half what it would cost you to create it from scratch. Price per copy was $500,000, plus annual maintenance. Not only did the big banks buy, but major mortgage servicers decided they could end-run the banks by taking the loans and ramming them through the grinder themselves.
    For a decade, every firm had written its own proprietary structuring tool for securitizing mortgages. Now we had commoditized it. Firms liked using the same piece of software. Intex became the King of Mortgages. Bonds were traded without showing up on the Bloomberg screens!
    Up until that point, almost all my securitization work had involved prime mortgages—those mortgages given to people who had an extremely high probability of paying them back. When a client wanted me to enhance my software to include “subprime” debt, well, that was something new, and I have to admit, I was kind of excited. This would greatly enlarge my universe of clients, because the subprime market was then split among many smaller players, each of whom needed my software.

    I quickly learned how fishy this world could be. A client I knew who specialized in auto loans invited me up to his desk to show me how to structure subprime debt. Eager to please, I promised I could enhance my software to model his deals in less than a month. But when I glanced at the takeout in the deal, I couldn’t believe my eyes. Normally, in a prime-mortgage deal, an investment bank makes only a tiny margin. But this deal had two whole percentage points of juice! Looking at the underlying loans, I was shocked.
    “Who’s paying 16 percent for a car loan?” I asked. The current loan rate was then around 8 percent.
    “Oh, people who have defaulted on loans in the past. That’s why they’re called subprime,” he informed me. I had known this guy off and on for years. He was an intelligent, articulate, pleasant fellow. He and his wife came to my house for dinner. He had the comfortable manner of someone who had been to good schools—he was not one of the “dudes” trying to jam bonds into a Palm Beach widow’s account. (Those guys were also my clients.)
    “But if they defaulted on loans at 8, how can they ever pay back a loan at 16 percent?” I asked.
    “It doesn’t matter,” he confided. “As long as they pay for a while. With all that excess spread, we can make a ton. If they pay for three years, they will cure their credit and re-fi at a lower rate.”
    That never happened.
    In 2001, when my five-year contract expired, Intex let me go. I guess I had become too expensive, and Intex thought they’d be fine without me. Why I had been able to retire at 45 for simply writing a computer program befuddled me and aggravated others who felt they had worked as hard. Life is not always fair, I told them. Right place at the right time. Besides, I explained, the mortgage market is as big, if not bigger, than the stock market. When they screwed up their faces in disbelief, I told them to look around. Every house, every building, every car, plane, boat, and piece of plastic in your wallet has a loan tied to it. It’s all about cash flow.
    Within a few months, the World Trade Center was attacked. The country became single-minded in its concerns. As segments of the economy weakened, the American home carried the day. Prices soared, more homes were built, everyone bought granite countertops, new plumbing, new mortgages. Home equity was the piggy bank. It kept Main Street working and Wall Street gorging. By 2003, more than $1 trillion in CMOs were being issued annually.
    Banned from Wall Street, I discovered that my summer house, on the North Fork of Long Island, included five acres of underwater land. I applied for permits to grow oysters. I had something to do. In many ways, farming oysters is more difficult, demanding, and frustrating than writing software. Errors take seasons and years to emerge, whereas software is instantaneous. Nature does not give you explicit warning messages; her ways are more subtle and take a lifetime to penetrate. I forgot the day of the week but knew instinctively the tide and the phase of the moon.
    Finance, however, is a larger drama. The daily tango of interest rates, money supply, and government debt continued to have an irresistible allure. By 2003, a financial-data firm approached me about writing a structuring tool for collateralized debt obligations, or CDOs. I asked my colleagues, what was a CDO exactly? Like CMOs, they were structured products, but the underlying collateral was not limited to home mortgages. They could be anything—corporate bonds, subprime-mortgage bonds, swaps, or simply air, like the synthetic CDOs: They could be CDOs underwritten by the bonds of other CDOs, CDOs squared. Chicken, pork, offal, chitterlings, tofu salad, fish guts—anything could be run through the grinder. “Diversity of collateral” was the pitch. Some things could go bad, but not everything at once. It never has, except during the Depression, and we’re so much smarter now. That could never happen again.
    With prime mortgages, the complexity of the structure is on the bond side: tweaking and fitting hundreds of different bonds from the same bundle of mortgages. But when the underlying collateral is subprime, or the subordinated bonds are supporting several subprime-mortgage deals, then the difficult task is deciding when and if these loans will go under. Default models were the rage. Throw some epsilons and thetas on a paper, hoist a few Ph.D.’s behind your name, and now you’re an expert in divining the future

    As much as anyone, I had already chased that. Why was I doing it again? As crude as it may sound, I can’t say I was motivated by anything more than the opportunity to make more money. It was sitting there, for me to take, and even for a relatively private person like me, who never dreamed of building my own castle in Greenwich or anything like that, it was hard to resist.
    Fortunately for me, Intex threatened to sue. They claimed that CDOs were so similar to CMOs that my noncompete applied. To take the job would mean a legal battle. In a sense, I was saved from my own base instincts. But my oystering permits had been approved. When I looked at myself in the mirror, after working all day hauling 400-pound cages of oysters off the bottom, I looked healthier and more satisfied than I ever remember being when I wore $3,000 Versace suits and thought of myself as a Wall Street success story.
    So that’s where I was when the world I had helped create started falling apart. I hadn’t anticipated it, but at the same time, nothing about it surprised me.
    Last month, my neighbor, a retired schoolteacher, offered to deliver my oysters into the city. He had lost half his savings, and his pension had been cut by 30 percent. The chain of events from my computer to this guy’s pension is lengthy and intricate. But it’s there, somewhere. Buried like a keel in the sand. If you dive deep enough, you’ll see it. To know that a dozen years of diligent work somehow soured, and instead of benefiting society unhinged it, is humbling. I was never a player, a big swinger. I was behind the scenes, inside the boxes. My hard work, in its time and place, merited a reward, but it also contributed to what has become a massive, ever-expanding failure. For that, I must make a mea culpa. Not a mea maxima culpa, mind you, but some measure of responsibility, a few basis points of shame. Give my ego a haircut.
    It hurts when people say I caused this mess. I was and am quite proud of the work I did. My software was a delicate, intricate web of logic. They don’t understand, I tell myself. Perhaps it was too complicated. But we live in a world largely of our own device. How to adjust and control these complexities, without stifling innovation, is the problem.
    The other day, Professor Gesiak brought me a pitcher of his basement-brewed beer, bartering for oysters. He mused that the U.S. government would, like Poland’s, make the currency worthless. What do we have, I wonder, that like the vodka in communist Poland, can be counted on to hold its value in this age?

  5. MARS Explained
    What do you think of this Neil?

    Marketing mortgages on MARS.
    By Lebowitz, Jeff
    Publication: Mortgage Banking
    Date: Sunday, November 1 1992

    This system may be the prototype for the way mortgages are marketed routinely in the not-too-distant future. It’s new-age technology married to mortgage processing, and it even sounds borrower-friendly.
    DURING 1992, A NUMBER OF major national lenders began to use the Mortgage Analysis and Reporting System (MARS), a new state-of-the-art system for delivering residential mortgages. MARS is the brainchild of two professors from the Wharton School of the University of Pennsylvania, Jack Guttentag and Gerald Hurst, and a Wharton business school graduate, Allan Redstone, who joined the firm (GHR Systems) in 1988. The MARS system started out very much in the realm of technology, but in time evolved into a solution to a set of very complex business problems.
    The original version of MARS focused on mortgage design and counseling using sophisticated graphics. It generated a lot of “oohs” and “ahs,” including some from this author when I first saw the system several years ago, but it didn’t generate many sales. This was partly because it was a “stand-alone” product for use alongside a lender’s existing processing system. Lenders usually don’t find stand-alone products that appealing, no matter how slick. In addition, it didn’t address some of the most important of lenders’ business needs.
    But in taking their lumps while canvassing the market, GHR also listened to what some of the more thoughtful market practitioners told them. What they learned was that flexible mortgage design capacity and sophisticated counseling functionality were important, but by themselves, they counted for little. What was needed was to integrate these features into a system that met other important business needs as well.
    These needs were spelled out in Guttentag and Redstone’s article “In the Year 2002” in the October 1992 issue of Mortgage Banking. They include rapid and error-free information transmission, complete pricing and underwriting, quality control and multi-lender capability.
    GHR also realized that the basic MARS architecture they had laid out for mortgage design and counseling could be extended to support all the other features on lenders’ wish lists. And so they persevered and set about adding these extensions. The result was the current version of MARS, which has had an altogether different reception than the earlier one.
    The MARS system architecture
    The MARS system consists of four major components:
    MARS Back Office is where mortgage program information is entered. (Usually the computer that MARS Back Office is loaded onto will be located in the lender’s main office, and seldom would a lender require more than one such installation.) The mortgage information entered includes the type of program, rates and other terms, qualification requirements, buydown and mortgage insurance options, closing costs and modifications in pricing and qualification requirements associated with different borrower and property characteristics.
    MARS Point-of-Sale (POS) is used in dealing with customers at the point-of-sale. Among other things, the originator can counsel actual and potential borrowers, qualify them, register loans, print documents, take applications and transfer them to the lender’s processing system and receive status reports on loans in process.
    MARS Clearinghouse is a computer network that is accessed by data providers, or in this case lenders, and by data users, who might be loan officers, correspondents or Realtors. Data providers offer mortgage products at terms entered on the clearinghouse computer, provide information on the status of loans in process and receive registrations and applications from data users. Data users are those at the point-of-sale who dial into the clearinghouse to retrieve information on the mortgages being offered and on the status of mortgages in process, and who send registrations and applications to data providers. This system is tied to Compuserve, a national wide-area network, which makes it accessible to both providers and users via local telephone calls.
    MARS Interfaces are customized modules that permit information to flow back and forth between the MARS components and a lender’s existing pricing, processing and other computer-based systems. The MARS Pricing Interface, for example, automatically transfers mortgage prices from the lender’s pricing program (usually spreadsheet-based) into MARS Back Office.
    An overview of how information is distributed through the MARS system by a single lender is provided by Figure 1.
    * Complete structural and price information about each loan product is entered into MARS Back Office. This is a one-time job with only occasional changes required when nonprice terms are changed or new products are offered.
    * Prices in MARS Back Office are updated automatically from the lender’s pricing system through the MARS Pricing Interface. This might be done weekly, daily or even more frequently when markets are volatile.
    * From the lender’s main office (or wherever prices are set), the information in MARS Back Office is uploaded to the MARS Clearinghouse.
    * From the lender’s origination site, the same information is downloaded to a terminal containing MARS Point-of-Sale.
    * Applications and registrations from the origination site can be transferred to the lender’s processing system through the MARS Clearinghouse using the MARS “To-Processing” Interface.
    * Information regarding the status of applications in process can be transferred from the lender’s processing system to the origination site through the MARS Clearinghouse using the MARS “From-Processing” Interface.
    A multiple lender system
    Multiple lender capacity is a critical feature of the MARS system architecture. The system can deliver loans from multiple lenders to the point-of-sale without hurting service quality. Each lender on the system uploads product information to the clearinghouse. In the multi-lender application, the user at the point-of-sale downloads information, in a single pass, from all the lenders who have authorized that specific user. An application or registration from the origination site is routed through the clearinghouse to the processing system of the particular lender whose product has been registered. And status information is received at the origination site, covering any or all loans from all lenders doing business with the user, in a uniform format.
    Complete program specification is another critical feature of the system. MARS allows lenders to define all the quantifiable features of any type of loan program in MARS Back Office, and then to use this information in MARS POS to counsel and qualify customers, register and take applications quickly and without error.
    MARS accommodates every type of mortgage and, within mortgage type categories, a wide range of variants off the standard design. For any loan program, rate/price modifications can be specified based on rate-lock period, LTV, loan size, the state and/or zip code of the prospective property, borrower characteristics, property characteristics, branch designation and interactions between these factors. Any loan program can include permanent and temporary “buy-downs” (such as 3-2-1, 2-1, or “compressed”) and mortgage insurance options. Underwriting requirements can be modified in the same way as prices for any characteristics or combination of characteristics of borrowers, properties or geographical area specified by the lender.
    The ability to price completely
    The complete program specification feature of MARS allows lenders to define prices and underwriting requirements in a way that reflects all the information the lenders have available. The following examples illustrate some adjustments made by lenders using the system:
    * On mortgage type A, points vary among 43 geographical areas defined in terms of zip codes. On mortgage B, points vary among 13 areas.
    * On mortgage C, points rise by 0.125 percent for each 20-day extension of the rate-lock period beyond 30 days, whereas for mortgage D, the comparable increments are 0.175 percent for each 15-day extension beyond 20 days.
    * On mortgage E, condo loans are illegal everywhere, but on mortgage F, condo loans are legal in 35 of 65 areas; however in 21 of those 35 areas, mortgage F condo loans carry a 0.5 percent increment over the base rate and a 90 percent maximum LTV; while in the remaining 14 areas, they carry a 1 percent rate increment and an 80 percent maximum LTV.
    * Nine rate-point combinations are offered, with the higher rate loans carrying larger increments in points for successive 15-day extensions of the rate-lock period.
    * Investor loans carry a 0.5 percent rate increment; condo loans carry a 0.25 percent rate increment, and investor condo loans carry a 1.1 percent rate increment, except in Philadelphia where they are illegal.
    Price adjustments at the point-of-sale
    The ability to price completely wouldn’t be worth much if loan officers were overwhelmed with complexity at the point-of-sale and had to fumble to find the terms applicable to a particular customer. The result would be delays and mistakes that would trash the system. But that doesn’t happen because this point-of-sale system is extremely easy to use.
    While loan officers have access to the full range of terms and requirements for each loan product–which in some cases may fill 10 or more screens of data–they never have to look at it unless they want to. MARS finds the right terms for a particular transaction automatically, as soon as the loan officer enters the needed information about the customer. For example, to get the right terms on any loans listed above, the loan officer need only enter the zip code of the property, the customer’s desired rate-lock period, whether it’s a condo, and whether the borrower is an investor. MARS does the rest.
    Counseling capacity
    The system deals with four broad categories of customers: information seekers, shoppers, buyers and refinancing owners.
    Information seekers are looking for quick answers about prices and terms. Loan officers help them using the MARS Electronic Product Manual (EPM), which allows immediate responses to price and product questions, adjusted for specifications as to borrower/property/loan type/area and the like, which the customer provides.
    For example, using EPM, a loan officer with a substantial menu of products could answer the following question in about 20 seconds:
    What is the lowest initial rate you have on a one-year ARM with no points, $250,000 loan amount with 90 percent LTV, 45-day commitment lock, on a single-family detached, for occupancy, located in zip code 19481?
    Customers who want information about loans for which they qualify are divided into shoppers who have not yet purchased and are interested (among other things) in how much they can spend; and buyers who have purchased a house and are looking for the most advantageous way of financing it. In the MARS system, counseling and qualification constitute a single process, so both shoppers and buyers are counseled only for products and terms for which they qualify.
    Matthew Broderick, who developed the HomeNet CLO, has since joined GHR. Broderick sees this single process as a major conceptual advance over the counseling systems used by HomeNet and others. These other systems require borrowers to choose a loan type and desired loan features and then check to see if they qualify, whereas the MARS system requires no prior choices. What it does is allow the customer to compare alternative programs with respect to a wide variety of performance criteria that the borrower can select, such as:
    * Maximum affordable sale price (for shoppers only);
    * Initial required cash investment;
    * Initial monthly housing expense;
    * Future housing expenses, including alternative scenarios for ARMs;
    * Effective interest cost (or total interest payments) over the borrower’s expected time horizon, including alternative scenarios for ARMs;
    * Future loan balance/equity in house, including alternative scenarios for ARMs.
    From side-by-side comparisons of different programs with respect to these types of performance measures, the borrower can make a choice.
    Loan officers can tell shoppers not only how much they can afford to pay using each mortgage program, but also how much cash they need to afford a home at a certain price. These are far more than rough estimates because they take into account not only prospective borrower’s (and co-borrower’s) available cash, income and exiting debt, but also any special property/borrower characteristics that affect loan terms, gifts or seller contributions and detailed closing cost estimates based on state and/or zip code of the property.
    Loan officers can qualify buyers in the manner the consumer prefers:
    * By desired LTV;
    * By desired loan amount;
    * By the desired down payment amount in dollars;
    * By total cash outlay the buyer wants to make in the transaction (covering points, mortgage insurance and all other settlement costs as well as down payment);
    * By searching for the minimum cash investment possible in the transaction.
    For refinancing homeowners not wanting to take out any cash, the system computes the new loan amount (for every selected refinance program) that exactly pays off the old loan, plus all refinance charges. For those wanting cash, the system offers three ways to qualify:
    * “Specify cash out”–MARS computes the new loan amount that results in the specified cash out after paying off the old loan and all refinance charges;
    * “Maximum cash out”–MARS computes the maximum cash out possible for all selected programs;
    * “Specify new loan amount.”
    However the customer qualifies, the system compares the existing mortgage to new mortgage options, with respect to the same features that are available to shoppers and buyers. MARS also shows the “break-even period” for each new mortgage–the period that the owner will have to retain the mortgage to realize a cost savings from the refinance.
    Quality control and cost
    Quality control is reflected in the overall system design of MARS, as well as in the thousands of details that makes up a mortgage delivery system.
    Information input–Putting information into a system entails significant cost to the extent that it must be done manually and it is a major potential source of errors that can be costly to fix. But the MARS system minimizes these problems, both at the back office level and at the point-of-sale:
    * Complete loan program specification from MARS Back Office to MARS POS avoids the need for subsequent telephone calls or faxes for information that’s been omitted;
    * Daily price updates are entered into MARS Back Office automatically through a pricing interface, avoiding the possibility of input error.
    * At the point-of-sale, loan officers key in only transaction-specific information that is available then, and no piece of information has to be keyed in more than once.
    * Product-selection mistakes at the point-of-sale are minimized because MARS (rather than the user) finds the appropriate prices and underwriting requirements, and MARS does not allow the counselor to select a loan for which the borrower does not qualify.
    * MARS POS will not export an application to processing until it runs a gamut of more than 400 consistency and completeness checks.
    Price and program validity–Commitments issued against lapsed prices are the bane of mortgage banking. This system provides complete protection against this.
    * Prices in MARS POS have expiration dates and times, after which they are not useable. Then the loan officer must download a new set of prices from the MARS Clearinghouse.
    * When a loan is registered from MARS POS, the mortgage program ID in the registration is checked against the file for that mortgage program in the clearinghouse. If there is a discrepancy in terms, the loan officer receives a message to that effect and is told to download the mortgage program files from the clearinghouse and requalify the borrower.
    Information transmission–The clearinghouse uses state-of-the-art compression and error-correction techniques to ensure extremely high data reliability, even in remote areas with poor local telephone line quality. A file of 10 mortgage programs, including all the information described earlier, takes less than 20 seconds to download error-free. Daily updates are often faster because the clearinghouse only transfers products that have been changed since the previous downloading of information.
    Flexible mortgage design
    As noted earlier, MARS began life partly as a mortgage design tool. Hence, even before any of the other components of the system were developed, it had the capacity to define (in addition to all the products found in the market today) “price level-adjusted mortgages,” “combo mortgages,” “dual index mortgages” and other exotics that have not made a major dent in the U.S. market yet.
    It is easy to underestimate the importance of flexible mortgage design capacity in a loan delivery system. All systems have the capacity to deal with today’s products, but what will happen if the market demands a different type of instrument tomorrow? Systems in which the mortgage design feature has been “hard wired” for today’s products will require substantial and costly modifications. The MARS system will not have that problem.
    MARS loan officer
    As Guttentag and Redstone pointed out in the October issue, commissioned loan officers are a costly method of marketing mortgages, largely because their productivity is so low. The MARS system, however, makes possible a substantial increase in their productivity. Several major firms are equipping their loan officers with laptop computers loaded with MARS POS, modems and printers. It’s expected that in the future, these loan officers will be operating entirely out of their homes. The following might be a typical day in the life of such a loan officer.
    * In the morning from her home, she dials into the clearinghouse for price updates and for the day’s leads, which have been received at the central office and distributed to the most convenient loan officer.
    * Calling on a lead, she counsels, qualifies, takes the application and prints out the opening documents for the customer’s signature. This might be done at the borrower’s home or place of business, the loan officer’s home or at a Realtor’s office.
    * On the way home (or to the next lead), she drops the documents in the mail.
    * Wherever convenient, she connects the modem and sends the loan registration and the application to the processing center through the clearinghouse. Since only a local telephone call is involved, the customer may be happy to have this done from that location.
    * When the loan officer gets home, she finds messages on her answering machine inquiring about the status of loans in process. So she dials the clearinghouse again to get status updates, which she can immediately convey to her customers.
    The MARS-based CLO
    CLOs are systems for providing loan offerings of multiple lenders via computer terminals in Realtors’ offices. Beyond that, they have ranged widely in scope, from simple bulletin boards that posted rates and little more, to complete origination systems that included processing, underwriting and closing. Many of the best known of these networks have come and gone (e.g., Shelternet, Loan Express and Compufund), but a few, such as Rennie Mae and HomeNet, have hung on without having a major market impact.
    It seems likely that within the next year at least one MARS-based CLO will begin operations on a national basis. The MARS-based CLO will not have the multiple system deficiencies that have limited the scope and impact of past and existing CLOs.
    All-inclusive versus selective architecture–GHR’s Broderick makes the point that all past and existing CLOs have been all-inclusive in the sense that if there are 30 lenders on the CLO, the loans offered by all 30 are carried on the terminals of every participating Realtor. An all-inclusive architecture has serious drawbacks:
    * Individual Realtors get access to offerings of lenders who pay to be listed; these are not necessarily the lenders with whom they want to do business.
    * Lenders get access to the Realtors on the system, who are not necessarily the Realtors with whom they want to do business.
    * The number of lenders that can be accommodated on the system is limited by loan menu congestion.
    The MARS system architecture is selective in the sense that Realtors can select the lenders who will be represented on their terminals and vice versa. Lender A’s programs are distributed only to those Realtors with whom Lender A does business. Lender B’s programs are distributed to the Realtors with whom Lender B does business, and so on. Hence, the system supports and reinforces existing business relationships between lenders and Realtors, rather than forcing these relationships into a fixed form. Even Realtors located in different offices within the same Realtor firm can elect to deal with different lenders. Further, there is no limit on the total number of lenders that can be accommodated within a given CLO structure.
    The selective architecture of the MARS system lends itself to a national CLO within a single administrative entity. The complete pricing and flexible mortgage design capacities of MARS would also facilitate a national CLO, because lenders can easily incorporate different product offerings and prices at Realtor locations in different areas.
    System component integration–CLO designers must decide how they are going to deal with the fact that participating lenders use incompatible processing systems in their non-CLO operations. In the past, there seemed to be only two options, neither attractive. The CLO could require that lenders on the CLO all use the same system, in which case lenders were forced to operate two systems; or the CLO could allow lenders to use their own systems, in which case both lenders and Realtors had to forgo the important potential benefits associated with an integrated system.
    A MARS-based CLO allows lenders to use their existing processing systems, but can tie them together through interfaces so the benefits of an electronically integrated system can be enjoyed by both lenders and Realtors. For example, Realtors can get application status information using a uniform format, despite the fact that the different lenders with which the Realtor deals use different processing systems. Realtors may obtain status reports on individual loans or a wide variety of general reports on all loans in process. Similarly, lenders can register loans and transfer applications electronically from the terminal in the Realtor’s office into their own processing systems.
    Operating efficiency and functionality–Realtors would enjoy the same operating advantages of the MARS system as other users. These include powerful counseling capacity; ease of use; error-free, rapid and complete information transmission; up-to-date prices; immediate document distribution and requests for credit reports, appraisals and the like from the brokerage office; and continual access to application status at the Realtor’s office. In addition, applications and registrations taken at the Realtor’s office will be transferred electronically to the individual lender’s own processing system.
    The MARS-based wholesaler-correspondent relationship
    The rapid growth of wholesaler-correspondent relationships in recent years reflects the many advantages of this mode of delivering mortgages. Yet, the system has some serious weaknesses as well, which is partly why several national wholesalers soon will begin distributing information to correspondents using MARS. The following are some of the major problems associated with the current methods of disseminating wholesaler-correspondent information and how MARS deals with them:
    Current: The formats used to provide information to correspondents, both in the technical manual and daily price sheets, vary from wholesaler to wholesaler. This creates numerous problems for correspondents in retrieving technical information about particular products and comparing the offerings of different wholesalers.
    MARS: Information received from wholesalers is in a uniform format. Hence, confusion is minimized about the similarities and differences between mortgages from the same wholesaler, and across mortgages from different wholesalers.
    Current: Because of the complexity of product information, correspondents sometimes commit to make loans at prices that no longer apply or loans that do not conform in other respects to wholesaler requirements. Such loans will be rejected by the wholesaler.
    MARS: Correspondents using MARS POS cannot register a loan that does not meet the wholesaler’s requirements, as explained earlier.
    Current: Correspondents often register the same loan with more than one wholesaler, which increases the difficulty that wholesalers have in managing their pipelines.
    MARS: Immediate electronic confirmation that a loan registration meets the wholesaler’s requirements removes much of the incentive for duplicate registrations. If needed, a procedure for capturing and reporting multiple registrations can be instituted when a critical mass of wholesalers is on the MARS system.
    Current: Because the information received from wholesalers is on hard copy, it must be further processed by the correspondent (by calculator or computer) in order to generate information required by customers, such as amortization schedules, disclosure documents, etc. The task of keying in data from different wholesalers who use different data formats is time consuming and error prone.
    MARS: Information received from wholesalers is not only in a uniform format, but is all ready to be used for counseling and qualifying customers, taking applications, and the like. The full power of MARS POS is available to each correspondent.
    Current: Because the information covering all mortgage programs and all modifications is voluminous, the information delivered by the current method of distribution typically is incomplete. Rate sheets, for example, may contain only the rates for the most popular mortgage programs. Updates on other programs must be obtained by telephone, which can cause errors.
    MARS: Program information distributed through the MARS system is complete. Hence, correspondents have much less need to call wholesalers for updates, amplification and clarification.
    What makes the MARS system exciting is its capacity to accommodate new and better ways of doing business. Embedded in the system is a vision of how rational lenders would want to operate if they were not subject to system constraints. Complete pricing is an obvious illustration of this principle, but there are many less obvious ones that lenders discover as they work with the MARS system. (For example, they may discover that there are substantial benefits in shifting functions out of processing to the point-of-sale, a shift that MARS accommodates.) What makes the MARS system practical is that it allows lenders to improve their efficiency while keeping the way they do business unchanged. Forays into the future can be taken a step at a time, which is (understandably) the way most lenders want to do it.
    Jeff Lebowitz is president of Strategic Systems Partners, Chevy Chase, Maryland.

  6. Please , Stern and his fellow mill’s were made rich by Tax Payer dollar’s funneled through Fannie Mea… lets not forget that Stern got his grooming at the firm of Gerald Shapiro… grand daddy of the LOGS ake Law Offices of Gerald Shapiro, nationwide network of foreclosure Mills… and least not lets not overlook that Stern was “voted” attorney of the Year in 1998 & 99 by Fannie Mea!!!!

    Nice to know the American Taxpayer is funding his grand lifestyle, and an IPO offering in short based on the foreclosing of America, no matter what it takes.

  7. Now the fraud has affected Florida Orange Growers

    This is how empires fall. Fraud and corruption.
    you dont know what the collateral damage is

  8. FABULOUS posting (DB document) B Davies. Thank you!!!!! This is one more nail in their coffin and certainly ammo in my case.



  10. I simply can not wait for the following press release:

    The AP reports that today Mr. David Stern, former Chairman of DJSP was found guilty of 100,000 counts of wire and mail fraud. A Florida Federal Judge, the Honorable Rufas Hangem High sentenced Mr. Stern to 42,249 years in prison and stated in his sentencing memorandum:

    “La cárcel es ahora su casa”

    (Prison is now your home)

  11. This was planned by Stern. Planned long ago. Nothing new here to Stern for sure. His exit plan was cemented before he cashed those checks from Wall Street.

    This is a real life Grisham novel for sure.

  12. Let’s not kid ourselves. If Stern dismantles his satanic little workshop, he’ll just re-emerge as some other company owned by an LLC, which is a subsidary of some corporation, which is owned by a DC trust which is owned by an offshore trust in the caribbean which is owned by an off-planet trust on Mars all run by agents of agents of agents.



  14. I can’t wait to see who is going to make all the new fake documents moving forward…

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