by Calculated Risk on 3/20/2007 10:29:00 AM

In a research note this morning, Bank of America Securities analyst Daniel Oppenheim wrote that mortgage lending problems go "well beyond subprime" are "likely to cut 15% of demand" for New Homes.

"Our view is that the excess inventory of homes for sale (the primary issue) and the reduced demand from tighter lending will lead to lower prices and likely exacerbate mortgage delinquencies and foreclosures," wrote Oppenheim.

See MarketWatch: Stricter loans seen draining new-home demand for more.

Meanwhile, MarketWatch reports that Citigroup remains bullish: Bullish home-builder analyst sticking to guns

One of most consistently bullish Wall Street analysts covering home builders during the housing downturn argues that the hand-wringing over the subprime-mortgage market and its potential impact on the already beaten-down group may be exaggerated.

"The threat from the subprime issue on home builders is obviously large, but somewhat indirect," wrote Citigroup analyst Stephen Kim in a research note this weekend. "It is also widely discussed and prone to hyperbole."

by Calculated Risk on 3/20/2007 08:41:00 AM

The Census Bureau reports on housing Permits, Starts and Completions. Seasonally adjusted permits declined:

Privately-owned housing units authorized by building permits in February were at a seasonally adjusted annual rate of 1,532,000. This is 2.5 percent below the revised January rate of 1,571,000 and is 28.6 percent below the February 2006 estimate of 2,147,000.

Starts rebounded:

Privately-owned housing starts in February were at a seasonally adjusted annual rate of 1,525,000. This is 9.0 percent above the revised January estimate of 1,399,000, but is 28.5 percent below the February 2006 rate of 2,132,000.

And Completions declined significantly:

Privately-owned housing completions in February were at a seasonally adjusted annual rate of 1,664,000. This is 9.4 percent below the revised January estimate of 1,836,000 and is 18.4 percent below the February 2006 rate of 2,038,000.

Click on graph for larger image.
The first graph shows Starts vs. Completions.

As expected, Completions are now following Starts "off the cliff". Completions are the key number in this release, since employment follows completions.



This graph shows starts, completions and residential construction employment. (starts are shifted 6 months into the future). Completions and residential construction employment are highly correlated, and Completions lag Starts by about 6 months.

Based on historical correlations, it is reasonable to expect residential construction employment to follow Starts and Completions "off the cliff". It is reasonable to expect significant residential construction job losses over the next several months.

by Calculated Risk on 3/19/2007 04:13:00 PM

Professor Kash has a followup: How Exposed Are Banks to Real Estate?

My earlier post: Commercial Bank Exposure to Real Estate

by Calculated Risk on 3/19/2007 01:13:00 PM

From Tanta:

Brian asked, in the comments to an earlier post regarding FICO scores, why mortgage lenders have not developed a “mortgage score” that would address the deficiencies in FICO when it comes specifically to mortgage underwriting. In fact, such attempts have been made and have never really gotten off the ground. It’s a very good question, though, and since the last time I launched onto a giant long Nerdish explanation of some dorky mortgage matter, some serious coin dropped into the CR tip jar, it occurs to me that you all deserve another one. This is, my dears, by way of thanking you all for the tips. It goes straight to my coffee-and-chocolate budget, which just then produces more lengthy posts. My story is that that’s a virtuous cycle, and I’m sticking to it.

The main reason that mortgage scores never got far, in my view, is the development of automated underwriting systems (AUS). The earliest attempts at building an AUS, in the late 80s and early 90s, used some sort of internal credit scorecard. By the mid-to-late 90s, when Freddie Mac and then Fannie Mae were perfecting their AUS, FICO scores had become an easily and widely available “credit scorecard,” and so the development path of these AUS changed, from the idea of creating a new credit scoring method for mortgages to creating the additional rule sets and algorithms needed, beyond the analysis of a borrower’s consumer credit history, to fully analyze mortgage loans. In other words, the AUS were intended to be automated “holistic” analysis, not just more computerized credit scoring.

The history and development of AUS is fascinating (really, it is, my UberNerds). It is, however, beyond today’s scope. Let me just note that a few years ago, the general situation in the industry was that the systems of the GSEs (Freddie Mac’s Loan Prospector (LP) and Fannie Mae’s Desktop Underwriter (DU), both of which could also handle FHA loans via additional technology called FHA TOTAL Scorecard), were the gold standard for AUS in the conforming-balance prime loan world. But they were never designed to underwrite loans that are not eligible for delivery to the GSEs, including jumbos, no docs, subprime (outside of the A- stuff the agencies have special AUS capabilities for), and a lot of exotic product structures (like the Option ARM). So there was parallel development by large private investors of their own AUS, the two best-known and most reliable of which are Countrywide’s CLUES and GMAC-RFC’s AssetWise, both of which specialize in jumbo loan balances, Alt-A and subprime.

But while just about every lender, correspondent, and broker in the country could have access to LP or DU for very low cost, and needed to anyway for its GSE loans, you had to be a correspondent of Countrywide or RFC to get access to CLUES or AssetWise, and like anyone else Countrywide and RFC tended to expect you to sell them the loan if you used their systems to underwrite it. Other buyers of jumbo and Alt-A whole loans might appeal to these smaller loan originators, but those other buyers didn’t offer an AUS, which are very expensive to develop. There became a habit of originators using the ones everyone had access to and were familiar with, LP and DU, to underwrite loans that neither system was designed to accommodate. What happened is that the whole-loan buyers would create an “overlay” of rules that a jumbo or Alt loan had to meet, in addition to approval of the loan by LP or DU. A very odd hybrid of traditional and automated underwriting was born; Star Trek fans are free to imagine Borg drones (half organic, half machine creatures) invading the mortgage world. Resistance sure seemed futile there for a while.

I mentioned this on an earlier post about the new subprime mortgage guidance, but let me touch on it again: you can offer “reduced documentation” loans in two general ways, lender-directed or borrower-directed. Lender-directed means that the lender first looks at the loan as a whole, including the proposed loan amount, sales price and appraised value, borrower credit history, and the income, assets, and liabilities that are indicated (still just “stated” at this point) on the loan application, plus the treasure-trove of other information that is on a loan application (where you work, how long you’ve worked there, what other real estate you own, whether you have supplemental assets like retirement accounts or cash-value life insurance, etc.). If all of that looks good enough—or it all looks low-risk enough—the lender might decide that the income or assets can be verified with less documentation than is usually required, or perhaps even no documentation. For instance, what is “usually required” to count a loan as full-doc is that the borrower verify income for the last two years, as well as currently. For a salaried borrower, that would mean submitting the last two years’ W-2s, plus a current year-to-date pay stub. (If your pay stub doesn’t show year-to-date, you have to scrounge up enough of them to prove that your current pay is not just this week’s fluke, which can happen for hourly employees who might just have worked more hours than usual this week, or for borrowers who receive a bonus. The lender doesn’t want to know what you made in your best month ever, but what can count as “stable monthly income.”) After a review of the file, the lender might require the borrower to submit only the last pay stub, and allow him or her to skip hunting down the W-2s.

This isn’t really just “documentation relief,” to use an actual industry phrase that might well drive you nuts. (Relief? Like having to prove your income is some giant burden?) It is also often a way to allow a loan to be underwritten at a marginally higher income figure than would have been calculated with true “full doc,” because, as in the examples I listed above, a true full-doc loan might involve some income “averaging” to arrive at the “stable monthly income.” Your average monthly income over the last two years can, clearly, be higher or lower than your last month’s income. Traditionally, underwriters considered an upward trend to be favorable, as long as there were any reason to think it would continue, and a downward trend to be worrisome, generally requiring some good offsetting factor like a higher than usual down payment or a perfect rather than just acceptable credit record. You can see, then, that when you don’t get the two years’ W-2s, just the current pay stub, you aren’t doing any averaging; you are taking the additional risk that the current pay stub is distorting a trend. For most salaried borrowers, that’s not a huge risk. It can be a major risk when we get to commissioned borrowers, contract workers, and so on, who are not, we notice, getting to be smaller rather than larger percentages of the workforce pool. (It was a big problem in the NASDAQ bubble, when you’d get all these folks wanting to count recently exercised stock options as “stable monthly income.” Underwriters can be crankier than usual—in need of regular chocolate infusions—in January of any given year, because they see more than usual numbers of borrowers wanting to count the annual bonus as current monthy income.)

In any case, this kind of “lender-directed” program of doc relief is different from a borrower-directed program, in which the borrower comes to you and requests a low-doc or no-doc loan up front. The specific term for that is “adverse self-selection,” and it is much riskier than a lender-directed program. It also creates one of the big problems of using an AUS like LP or DU to underwrite these loans. LP and DU were designed to be lender-directed programs; they might allow some doc relief after the initial analysis is done, but they always start with the “assumption” that any number you type in for income or assets is verifiable if not initially verified. That’s a huge, important difference. The initial analysis can “give more weight” to things like DTI and reserves after closing if it can consider those things as potentially verified fact rather than quite possibly unverifiable smoke. It might “decide” to let those things remain unverified, or only partially verified, but it does so, if I can put it this way, because it knew it had the right to demand otherwise. A “borrower-directed” low doc loan simply messes up the whole underlying assumption of verifiability. And, of course, a borrower-directed low or no doc loan is, as we’ve seen, probably (although not necessarily, of course) already “gaming” the system: inflating the income or assets so that the DTI or reserve calculations come up with better results than they would have using verifiable numbers. The huge joke is that you can get the AUS offering “relief” to a borrower who qualified for that “relief” by lying to the system up front.

(It is possible, of course, to get around that problem by building in some algorithm that selects a certain number of loans to be forced into full doc, regardless of whether they might otherwise have been eligible for doc relief, to create some disincentive for gaming. I won’t say the GSEs aren’t doing that; I honestly don’t know, although I don’t see any signs that it’s working if it is happening. The problem, though, is making sure that such an instant-feedback fear of getting caught lying is applied enough for any individual user of the AUS to create the right Pavlovian behavior. Remember that the GSEs buy loans at the top of the food chain, mostly, from big seller/servicers and “aggregators,” who in turn buy their loans from smaller correspondents and fund loans for little brokers. The AUS gets used at the top of the chain and also at the bottom (the borrower entry level). So your algorithm would have to work by selecting a big enough percent of those little bottom-level pipelines of loans to scare any individual originator, as well as by selecting enough of the aggregator’s pipeline to scare the aggregator. This is by way of saying that we’re dealing with second- and third- and fourth-order effects of how the business structure, in “disintermediating” the process, finds a way to create a problem that the original software engineers didn’t have in their sights. You have to keep re-modulating your phasers, because the Borg adapts.)

In large part, that’s where this “hybrid” or Borg approach comes in: whole-loan investors did (mostly) realize that LP and DU were not designed to accommodate borrower-directed low doc or no doc loans. They’re also not designed to accommodate jumbos in a very important sense. Since LP and DU are designed to analyze loans the GSEs actually buy, their internal logic was designed, for instance, to weigh the proposed down payment on the loan with the assumption that the loan amount isn’t going to be higher than $417,000 (currently). A 20% down payment on a $471,000 loan is generally considered a compensating factor for other possible weaknesses (like tight ratios or a few minor credit dings). But a 20% down payment on a $1,000,000 loan? That might not even meet basic program guidelines; it might be possible, but it stops being a compensating factor and becomes a weakness that needs compensation elsewhere. In other words, a traditional view of things indicates that an 80% $1MM loan is the equivalent of a 90% or so conforming loan: possible, but definitely in the higher-risk bucket. But in a real sense LP and DU didn’t “know” that, because they weren’t designed to handle the problem. Ergo, you had the investor accepting these loans underwritten by the AUS, as long as it met a separate “overlay” or second hurdle of requirements to get around this problem.

Eventually Fannie Mae came up with the idea of “Custom DU,” which is a way a lender can access DU for loans that aren’t Fannie Mae-eligible by “customizing” its product eligibility features to take things like jumbo balances and borrower-directed documentation reduction into account. (You may ask why a GSE is putting such investment in technology to accommodate loans it is in no way chartered to buy. You may be asking about something like the concept of “corporate welfare,” where the private sector gets the quasi-government sector to subsidize its technology costs. But that’s another day’s problem.) This is still a fairly new development and, as far as I’m concerned, the results aren’t in yet (someone else might tell you different, of course). But we here at CR have now become quite wary of these things without a long enough performance history. And it’s not just history I want; there’s also the problem with the level of possible “customization.” The short version, for now at least, is that I am concerned that investors don’t know enough about the core logic of the system (the “black box” part) to know if the things that can be customized (product eligibility rules like maximum loan amount, documentation type, and so on) are 1) customized correctly and 2) sufficiently compatible with the core logic. The customization is done by the lender, and so it’s only as good as the lender’s inputs (there are competence issues here as well as potentially abuse and failure-to-test issues). Furthermore, you get back to the whole logic problem behind the lender-vs-borrower directed issue: at what level does too much customization defeat the purposes of the machine’s approach?

On an earlier post I talked about conforming loans as the vanilla ice cream of the mortgage business; I’ve also used the term “commodity” to describe them. The development of GSE AUS was spurred as much by the desire to keep its book of business uniform and homogeneous as much as to use technology to speed up and increase productivity of the loan approval process. The whole idea was that the AUS could sort out the vanilla ice cream from the mocha java praline mango. It is in no way clear to me that the eventual use of GSE AUS for nonconforming loans, with an overlay or with customization, was motivated largely by anyone’s desire to impose uniformity and homogeneity on the jumbo and Alt production. I personally believe that it was motivated more by two things, one more respectable and one less so: first, it was a desire to capture the speed and productivity increases of technology. Second, it was an attempt by at least some people to get the “seal of approval” of LP or DU on exotic loans—in other words, the “core logic” incompatibility was a feature, not a bug, to some folks. I’d start seeing that a lot in due diligence. I’d find some god-awful loan I’d throw on my problem loan list, only to have the originator come back and say, “Yeah, but we got a DU approve on that one.” My response was something on the order of “Yes, but you threw a loan at DU that was ‘over its head,’ as it were.” They did that for a reason.

So how do we get back to FICO? Well, the AUS out there—at least LP and DU—do not use FICO scores as such. The GSEs still require lenders to get them and report them on the loans, but the AUS do their own internal credit analysis based on raw data imports from an electronic credit report. That’s what I meant above by indicating that the development shifted away from creating a free-standing “mortgage score” to replace FICO. AUS do not need another “free-standing” score, because they’re designed to do the holistic underwriting themselves. They’re an attempt to automate what a traditional underwriter before FICOs did.

That’s what I meant in the comment section of this post when I indicated that, for mortgage people, FICOs traditionally were useful less as a predictive tool than a communication tool: it’s not so much that traditional lenders like the GSEs ever depended on FICO’s analytics to substitute for their own default estimates; it’s that FICO score became a handy, consistent, easily-available “shorthand” designation of a loan’s credit quality, insofar as over time they were “calibrated” to GSE loan performance, and the GSEs could then set the actual FICO “bucketing” guidelines (over 720, under 620, etc.). What that means, in essence, is that they were less important to traditional underwriters (people or machines) than they were to investors in traditional loans. As I suggested in this post, the giant MBS market works “efficiently” insofar as end-investors can really just make a lot of reliable assumptions about what’s going on in the details of processing the underlying mortgage loans (the “sausage factory”). By reporting such indications of credit quality as FICO, LTV, DTI, doc type, etc., a lender can “indicate” to a bond buyer what the general quality of the loans is, and the bond buyer can have a sort of “reality check.” The exact methods I use to get into the weeds with individual loans might be a matter of “rep and warranty,” but you, the end investor, can glance at the general stratification of the pool I supply you with, the FICO, LTV, etc., and you can check the plausibility of those reps and warranties. If I’m claiming to use “traditional” underwriting methods but I produce these pools with these low average FICOs, you might wonder what the hell I mean by “traditional.” You might be right to do so.

From using FICOs as a short-hand indication of credit quality, it was a short step to using them to price things. By price, I mean more than just setting the interest rate and points for an individual loan, or even the price of a security or tranche thereof. FICOs are involved in setting the required credit enhancement levels of a security (such as overcollateralization), the MI premium required, the due diligence level required, and any number of things that, basically, come out of the yield of a loan. I, actually, worry as much if not more about this issue than I do in using FICOs as part of the initial underwriting. We’ve had occasional discussions here on the blog about “guideline rationing” versus “price rationing” as mechanisms of credit crunching. That whole issue is about whether available credit is reduced as much by making it too expensive as by re-writing the guidelines so that people don’t qualify for certain kinds of loans. It’s a true chicken-and-egg problem, though. Suffice it to say, for now, that a large distortion may have entered the market during the boom because FICO (a kind of derivative or simplification of a complex credit analysis) drove a lot of pricing decisions. That, in short, is the “Alt-A” problem in a nutshell: not only did the FICO of those loans make them look like “prime,” it made people willing to price them at tiny risk premiums over prime. So pricing models have to get as complex as AUS models, and they have to be applied to the right kind of product, or else you have the same problem as I’ve indicated above with using LP or DU to underwrite a “nontraditional” loan. Borg pricing is as scary as Borg underwriting.

The rating agencies do have their own software—S&P’s Levels is generally the standard—that are supposed to account for pricing/credit enhancement levels on nontraditional product. I still think those models over-weight FICO, and that that’s a large part of why it seems that “Alt-A” is deteriorating “so fast.” There’s a whole issue out there about why, then, people aren’t using more AUS like CLUES or AssetWise, which were designed to handle Alt-A, but that kind of gets complicated by what we’re hearing from Countrywide and RFC about their own little Alt problems. Perhaps building an Alt AUS is harder than everyone thought? Perhaps speed and efficiency are more “expensive” than we thought? Perhaps you don’t have to be an outright Luddite to conclude that, maybe, we should give this tech fetish another thought? I have observed before now that I very often think we fail to consider certain kinds of tech in the mortgage business at its “true cost,” and that once you do that, you often find the vaunted cost savings and productivity increases kind of evaporating on you when your business adapts, like the Borg does, to whatever high-tech weapon you can fire at it. But I am known as an unassimilated thinker.

Tanta

by Calculated Risk on 3/19/2007 01:05:00 PM

Click on graph for larger image.

UPDATE: NABH Press Release: Builder Confidence Slips In March

Builder confidence in the market for new single-family homes receded in March, largely on concerns about deepening problems in the subprime mortgage arena, according to the National Association of Home Builders/Wells Fargo Housing Market Index (HMI), released today. After rising fairly steadily since its recent low last September, the HMI declined three points from a downwardly revised 39 reading in February to 36 in March.

“Builders are uncertain about the consequences of tightening mortgage lending standards for their home sales down the line, and some are already seeing effects of the subprime shakeout on current sales activity,” said NAHB Chief Economist David Seiders. “The fundamentals of today’s housing market still are relatively strong, including a favorable interest-rate structure, solid growth in employment and household income, lower energy prices and improving affordability in much of the single-family market – due in part to price cuts and non-price sales incentives offered by builders. NAHB continues to forecast modest improvements in home sales during the balance of 2007, although the problems in the mortgage market increase the degree of uncertainty surrounding our baseline (i.e., most probable) forecast.”

Derived from a monthly survey that NAHB has been conducting for 20 years, the NAHB/Wells Fargo HMI gauges builder perceptions of current single-family home sales and sales expectations for the next six months as either “good,” “fair” or “poor.” The survey also asks builders to rate traffic of prospective buyers as either “high to very high,” “average” or “low to very low.” Scores for each component are then used to calculate a seasonally adjusted index where any number over 50 indicates that more builders view sales conditions as good than poor.

All three component indexes registered declines in March after having risen in the previous month. The index gauging current single-family home sales and the index gauging sales expectations for the next six months each declined three points, to 37 and 50, respectively. Meanwhile, the index gauging traffic of prospective buyers declined a single point, to 28.

Regionally, the HMI results were somewhat mixed. In the Midwest and West, the index gained one point to 28 and 36, respectively. In the Northeast, the HMI declined two points to 41, and in the South, it fell four points to 40.

by Calculated Risk on 3/19/2007 12:26:00 PM

From Bloomberg (hat tip Brian): Fremont General Gives Mortgage Staff Two-Month Dismissal Notice

Fremont General Corp., the California thrift trying to sell its home-lending business, told the unit's staff they may be dismissed in two months.
...
"The company has aggressively been pursuing its options," Walker said. "Such efforts continue, although the company cannot provide more definitive information today."
...
California requires employers to give workers 60 days notice before "a plant closing or mass layoff," according to the state Employment Development Department's Web site.

by Calculated Risk on 3/19/2007 11:54:00 AM

From the OC Register: Homeowners face foreclosure

The United States likely will see 1.1 million foreclosures during the next six to seven years on adjustable-rate mortgages issued when home prices were at or near the peak of the market, a study released today by First American Corp. of Santa Ana says.

As a result, lenders will end up losing about $112.5 billion.

But that probably won't have a significant impact on the economy or the mortgage industry since the loss equals less than 1 percent of the $12 trillion in home loans projected for the next six years, the study said.

"This is not going to break the economy," said study author Christopher Cagen, director of research and analytics at First American CoreLogic, a First American company. "It's less than the price of alcohol. It's less than the price of gasoline going up to $3.25 a gallon. ... It's part of the business cycle and it's not going to be dominant."

Compare this to the Center for Responsible Lending report: Losing Ground: Foreclosures in the Subprime Market and Their Cost to Homeowners.

"... foreclosure rates will increase significantly in many markets as housing appreciation slows or reverses. As a result, we project that 2.2 million borrowers will lose their homes ...
...
We project that one out of five (19 percent) subprime mortgages originated during the past two years will end in foreclosure. This rate is nearly double the projected rate of subprime loans made in 2002, and it exceeds the worst foreclosure experience in the modern mortgage market, which occurred during the “Oil Patch” disaster of the 1980s."

I'm trying to find the First American study.

by Calculated Risk on 3/18/2007 04:18:00 PM

Professor Kash had an interesting post on Friday: Bad Loans, Banks, and the Coming Credit Crunch Kash is trying to look at the incipient credit crunch from the bank's perspective.

"I've been thinking about the health of the banking sector of the US economy, and pulled together a couple of charts that have gotten me thinking. And worried."

Check out Kash's post and graphs.

Kash presented the loan amounts in real terms. The following graph shows the loan amounts as a percent of GDP (Q1 2007 estimated).

Click on graph for larger image.

This graph shows the rapid increase in real estate loans. This category includes all loans collateralized by real estate, and includes residential, commercial and real estate construction and development loans.

The banking sector is clearly exposed to real estate, although the breakdown between residential and commercial isn't available.

Note: Commercial and industry (C&I) bank borrowing has risen recently as a percent of GDP, but the level is still low compared to historical norms. However this is bank loans only, and doesn't include any bonds. I'll have more on consumer borrowing soon.

We know, from the FDIC Semiannual Report that the concentration of CRE and C&D loans has increased:

Small and mid-size institutions have been increasing their concentrations in riskier assets, such as CRE loans and construction and development (C&D) loans. This suggests that, although small and mid-size institutions have been more successful in limiting the erosion of their nominal NIMs, they have achieved this success in part by assuming higher levels of credit risk.

... continued increases in concentrations and reports of loosened underwriting standards at FDIC-insured institutions signal the potential for future credit quality deterioration. In addition, regulators have noted increasing C&D and overall CRE loan
concentrations, especially at institutions with total assets between $1 billion and $10 billion.

The housing crisis is now front page news, but there is little discussion about U.S. bank exposure to CRE loans. If a CRE slump follows the residential real estate bust (the typical historical pattern), then the U.S. commercial banks might have a serious problem.

Currently delinquency rates are very low for CRE loans. But when times are tough, CRE loans usually have the highest overall delinquency rates.

I understand why Kash is thinking about this issue ... and why he is worried.

by Calculated Risk on 3/18/2007 02:47:00 AM

From CR: At the OC Register, Mathew Padilla interviews Glenn Stearns of Stearns Lending. Here is an excerpt:

Stearns also said there has been an inflation in credit scores, known as FICO scores. He said some consumers with a maximum of $3,000 in credit had a FICO of 700, which generally is considered a good score. Such a first-time buyer had no proven history of making a house payment, he said. In his own business, he said customers that went into default tended to have credit scores greater than 700.

“Everyone is having to rethink credit scores,” he said.

This makes it sound like FICO scores are undergoing a process like “grade inflation” in college. Tanta explains that the problem isn't with the FICO score itself, but that using the FICO score alone is insufficient for first time homebuyers.

The following is from Tanta:

Some of us (OldFart Mortgage, LTD) used to require a first-time homebuyer to have a 24-month rental history, and to verify that with a direct verification from the landlord or property management company. First, we would make sure that the borrower had a history of making housing (not “house”) payments on time. Then, we would calculate the borrower’s current housing expense as a ratio to gross monthly income, and compare it to the borrower’s proposed monthly housing expense (including taxes and insurance). The result of this comparison is actually what old-timers mean by the term “payment shock.” (The term for potential future issues on an ARM was “rate shock”; the press has completely muddled the terms now so much that it’s hopeless.) Anyway, the traditional rule of thumb was that a first-time homebuyer was limited to a proposed house payment no more than 150% of the current housing (rental) payment. That extra 50% allowed owning to be more expensive than rent, but also was conservative enough to allow for things like maintenance and other expenses that renters aren’t often in the habit of paying for. If you let them double their monthly housing payments, they can get into terrible trouble the first time they have to call a plumber. The theory is that second-time homebuyers have already learned this awful lesson and so they can be allowed more “shock” (as long as they still meet the total DTI max).

In any case, this verification of the rental payment history and “payment shock” test was on top of the required minimum FICO. So those borrowers described in the article—a nice pretty 700 FICO derived from one $3000 card balance—would not get the loan if they didn’t meet the other two tests. For instance, this old rule eliminated FTBs who were going straight from mom & dad’s place (or the dormitory) to a mortgage: they were ineligible because they couldn’t show a 24-month history of being responsible for their own housing costs. Ditto for someone “renting” a condo owned by the parents but not actually paying anything near a real housing cost burden. I used to get those “kiddie condo” deals a lot when I worked for a lender with branches in a college town.

In my view, it is among the most irresponsible of the irresponsible lending we’ve seen lately that FTB rules were relaxed to allow either 1) no history of making one’s own rental payments required or 2) not counting late rental payments as a reduction to FICO (they won’t affect the FICO if the landlord doesn’t report to the credit bureau, and small-time property owners don’t) or 3) the payment shock limit was increased to 200% or more.

That said, it’s not so much that FICOs get “inflated,” it’s that their importance to the loan qualification process is inflated. For anyone who has already owned a home, the mortgage payment history is already taken into account in the FICO (because mortgage servicers report to the bureaus). But first-timers present a cautionary tale in not letting the FICO bear more weight in your decision than it should.

I’m sure that’s probably what the guy in the newspaper meant, but as usual, the newspaper only deals in sound bites, so my version is just the one that shows the work as well as the answer, as it were. There are some other issues a lot of us have with FICOs; they can in some cases “reward” heavy debt users over limited debt users. That’s why a sane underwriter (yeah, right) reads the credit report instead of just looking at the FICO. The other side of this, you see, is that the borrower with $3000 on the cards might have a FICO of 700, but the borrower with $8000 on the cards might have a FICO of 750 (because that person’s credit record is older, or has more tradelines—the $8000 is split over three cards instead of one, and the more trades you have, generally, the higher your score until you get to the point where you’re maxed out). So just having stricter FICO rules for FTBs would end up setting the very perverse incentive of encouraging them to get into a lot of consumer debt so they can prove they’re good enough to get a home. I would rather go back to the (“inefficient”) old days where we used FICOs, but only as a guideline that had to be backed up with other considerations, positive and negative. I certainly don’t want to see young borrowers locked out of mortgage credit because they don’t have enough plastic in their wallets or because they bought an old beater for cash instead of taking out a car loan or lease for something new, for the love of Peat. But I fear that’s the message some of them have gotten.

And that gets us back to my long-standing problem with subprime lending becoming predatory lending. A lot of folk end up in subprime because they don’t have access to the kind of credit that would improve their FICOs enough to get them into prime. If you come from the side of town where the available credit is mostly payday lenders or rent-to-own stores—who don’t report to the bureaus—you are not only getting screwed on whatever borrowing you’re currently doing, because the rates are just usurious, you’re also screwed because paying those cruddy rates in a timely fashion doesn’t offer the reward of a good FICO score. My solution to a lot of the predatory lending problem is to make sure that depositories are offering “entry level” credit to low-to-moderate income people, including young people. If the banks get ahold of them before the sleazy credit card mailers or the local loan sharks do, they can get some debt experience in a safer and sounder manner. But some banks seem to have taken the position that they’ll let Providian or the local loan shark take the risk on entry level borrowers, and then they’ll pick out the few survivors for their prime loans, while putting the others into those high-yield subprime loans. When we focus exclusively on borrower behavior, without looking at lender behavior, we get a skewed view of how you “create” a subprime borrower in the first place.

by Calculated Risk on 3/17/2007 06:44:00 PM

Confusion about Option ARMs and other kinds of negative amortization keep coming up in the comments. If you really want to know how this stuff works, you should know up front that it’s a long story. If you’re not up for the long story, skip to the next post. I would never dream of holding it against you; the following is hard-core UberNerdism, and there’s nothing wrong with just being a normal reader of the blog. In fact, I envy you. Someday the rest of us will get help for our UberNerdism; until then . . .

With a regularly amortizing ARM, the rate adjusts on some schedule that is laid out in the original contract (the note). Take a 5/1: the rate adjusts after five years, and then every year thereafter. But because it is a regularly amortizing ARM, the payment adjusts after the rate adjusts, so that the payment is always enough to cover the interest due plus sufficient principal to retire the debt at maturity (that's the definition of "amortization"). With this loan, there are no "payment caps." There are "rate caps." This means some limitation on how high or low the rate can go at any given adjustment, or over the life of the loan. The lack of “payment caps” means that the payment must go as high (or low) as it needs to in order to satisfy the rate increase (decrease). If there’s “rate shock” in this loan, you feel it immediately, because you immediately begin making payments at the “shocking” interest rate.

Negative amortization loans can work by calculating two "rates": the actual accrual rate (the real interest charged) and the payment rate (a kind of "artificial rate" used to set the minimum payment). The payment rate might also be an “introductory rate.” Here’s an example of a neg am variant on the old 5/1 ARM. (Important: this is just an example. There are jillions of unique neg am ARMs out there, and the Option ARM is even more complicated than the following. Do not assume that the following example is how they all work in exact terms; it’s just how they work in overall concept.)

In our example loan, the introductory accrual rate is 1.95% for three months. This means that the first three payments are based on an actual rate of 1.95%, and so for three months the loan amortizes (the payment due is equal to the payment required to satisfy all interest and a portion of principal.) Let’s assume a loan with an original balance of $90,000 used to purchase a property with a sales price of $100,000. For the first three payments, you get this:

#	Beginning Balance	PMT Rate	Minimum PMT	Accrual Rate	Accrued Interest	Scheduled principal	Short- fall	Ending Balance	Original Prop Value	LTV
1	90,000.00	1.95%	($330.41)	1.95%	($146.25)	($184.16)	0.00	89,815.84	100.000.00	0.9000
2	89,815.84	1.95%	($330.41)	1.95%	($145.95)	($184.46)	0.00	89,631.38	100,000.00	0.8982
3	89,631.38	1.95%	($330.41)	1.95%	($145.65)	($184.76)	0.00	89,446.62	100.000.00	0.8963

After three months, the accrual rate changes to 6.50% for the remaining 57 months of the initial 5-year period. However, the minimum payment remains fixed for the remaining 57 months.* What this means is that the minimum payment required is calculated at a lower rate than the actual accrual, and so if the borrower makes the minimum payment, the loan negatively amortizes, meaning that the difference between interest accrued at 6.50% but paid at 1.95% is added to the loan balance. The borrower is not forced to make the minimum payment, although of course we’re seeing people take these loans precisely because they can’t afford the amortizing payment. You can see right here that the borrower already got “rate-shocked” in real terms, going from 1.95% to 6.50%. The borrower just doesn’t feel rate-shocked, because by making the minimum payment, the borrower is in essence borrowing enough money each month to subsidize the debt service.

Here’s what the loan looks like (condensed) for the remaining 57 months. I have broken out the “fully amortizing” payment at the accrual rate into its principal and interest components; the required payment from the borrower to actually amortize the loan (satisfy all interest due plus retire some principal) would be the total of the two. If the loan were an Option ARM with the choice of making an interest only payment rather than a fully-amortizing or negatively-amortizing (minimum) payment, the required IO payment would be the portion shown below as “accrued interest.” This chart shows the “shortfall” as the total difference between the amortizing payment and the minimum payment; the ending balance, however, is equal to the beginning balance less the difference between “accrued interest” and “minimum payment” (because “scheduled principal reduction” does not happen with a minimum payment). An alternative way to calculate that is to subtract the scheduled principal from the beginning balance, then add back the entire shortfall (not just the interest shortfall) to get the ending balance. (You may wish to have a drink before continuing.)

#	Beginning Balance	PMT Rate	Minimum PMT	Accrual Rate	Accrued Interest	Scheduled principal	Short- fall	Ending Balance	Original Prop Value	LTV
4	90,000.00	1.95%	($330.41)	6.50%	($484.50)	($82.41)	(236.50)	89,600.71	100.000.00	0.8945
5	89,600.71	1.95%	($330.41)	6.50%	($485.34)	($83.07)	(238.00)	89,755.63	100,000.00	0.8960
6	89,755.63	1.95%	($330.41)	6.50%	($486.18)	($83.74)	(239.51)	89,911.40	100.000.00	0.8976
...
56	98,673.00	1.95%	($330.41)	6.50%	($534.48)	($127.42)	(331.49)	98,877.07	100.000.00	0.9867
57	98,877.07	1.95%	($330.41)	6.50%	($535.58)	($128.54)	(333.71)	99,082.24	100,000.00	0.9888
58	99,082.24	1.95%	($330.41)	6.50%	($536.70)	($129.67)	(335.96)	99,288.52	100.000.00	0.9908
59	99,288,52	1.95%	($330.41)	6.50%	($537.81)	($130.82)	(338.22)	99,495.92	100,000.00	0.9929
60	99,495.92	1.95%	($330.41)	6.50%	($538.94)	($131.98)	(340.50)	99,704.45	100.000.00	0.9950

You notice here that the ending balance of the loan after 60 payments is $99,704.45, or just over 110% of its original balance. This will become important below. Also notice that the LTV here is based on a constant original appraised value. You can make any changes you want to that original value and get a better or worse looking current LTV. But the contractual limitations on a neg am loan have to do with the relationship of current balance to original balance, not LTV. In the real world, of course, a borrower who is negatively amortizing at the same time that the appraised value of the property is dropping is getting much further underwater than this example indicates; I’m just trying to show effect on LTV if value stays constant.

After 60 months, the accrual rate adjusts to the formula of index plus margin, just like any other 5/1 ARM. However, the required payment after the first adjustment (at 60 months) is capped at 7.50% of the prior payment. If the adjustment to the new accrual rate would require a new payment greater than 107.5% of the old payment in order to fully amortize the loan, and the borrower makes the minimum payment instead, the loan negatively amortizes. The 7.50% payment cap is different from the rate cap. On a 5/1 ARM, the rate cap could be 5.00% at the first adjustment and 2.00% at each subsequent adjustment. What that means is that the rate will not increase more than five points at the first adjustment or more than two points at subsequent adjustments. If the initial accrual rate is 6.50%, at the first adjustment the rate will never be higher than 11.50% (6.50% plus five points). The payment cap, on the other hand, is a percent limitation, not points. In other words, to calculate the new minimum payment, you take the old payment and multiply by 1.075.

Using our example above, and assuming that the accrual rate increases only by 2.00% to 8.50%, the new fully amortizing payment is $802.85 ($706.24 interest plus $96.61 principal). However, the payment cap of 7.50% would limit the new minimum payment to $355.19 ($330.41 times 1.075%). On this example loan, that won’t actually happen, though. Keep reading; it just gets more complicated.

At each point, the amortizing payment is calculated on the actual loan balance outstanding. This is how neg am becomes turbo-charged ugly: if you make only the minimum payment each month, the difference between accrued and paid interest is added to your balance. Therefore, next month, your accrued interest is charged on a higher balance than last month—you are paying interest on interest. So neg am becomes “exponential” instead of “arithmetical.” It’s the reverse of compounding interest in a savings account.

So, in order to keep this exponential growth of the loan balance under control, the neg am ARM has “recast” mechanisms. These are separate from rate and payment caps and adjustments. One of the big problems with understanding all this is that too many people (including our fine media) use the terms “reset” and “recast” as if they were synonyms. You’ll never understand a neg am ARM if you do that. What we went through above was “resets” of the rate and payment. What we’re about to go through now is “recast.”

To understand recast, think of it as a process that is concurrent with but not on the same schedule as the reset process. Resets (adjustments to rates and therefore required and minimum payments) happen according to the pre-arranged terms laid out in the original note (such as every year after the first five years). But, contractually, the borrower is not required to negatively amortize; one can make the full payment, not just the minimum payment. (On an Option ARM, one can also make a full interest only payment; that doesn’t lower the balance, but it doesn’t increase it because all interest due is paid for the month.) One can also make occasional curtailments (lump sum payments of principal that don’t pay off the loan in full but that reduce its balance substantially). So for any given neg am loan, you can’t know ahead of time whether and at what point and how fast it will negatively amortize. By “how fast,” we are also referring to the magnitude of the interest rate adjustments. With any ARM, you cannot know in advance how much the rate might change at the first adjustment or any subsequent adjustment, because the new rate is determined by the formula margin (constant, spelled out in the note) plus index value (variable; the index chosen is in the note, but the actual value of it in the future is unknown). The higher the future accrual rate increases, the faster the loan will (potentially) negatively amortize.

So the “recast” provisions are a separate process of monitoring and forcing the restructure of the loan, over time, to make sure that any negative amortization doesn’t get too far out of hand. Recast provisions can be as complicated as resets, but here’s a common setup:

First, there is a provision to reamortize the loan every 60 months. What this means is that every five years, the servicer has to recalculate the minimum payment by ignoring those 7.50% payment caps. This may or may not produce huge payment shock to the borrower; it will depend on how significant the rate resets were in the preceding 60-month period, or, for the very first recast, how deep the discount was between the accrual rate (6.50% in our example) and the payment rate (1.95%). Remember that it is possible at any rate change date that the rate adjustment was small enough that the new required payment was less than 1.075% of the old payment. It is of course possible that it wasn’t, and this can hurt. In any case, this 60-month recast brings the minimum payment up to fully amortizing, but it doesn’t cancel out the regular rate and payment resets that can happen in the next five years as outlined above. So, with an ARM with annual accrual rate adjustments, the 60-month rolling recast keeps the loan amortizing for the following year; after that, neg am could start happening again (until the next 60-month recast). Think of it as a way of “catching the borrower up” every five years, but allowing them to start “getting behind again” eventually. So that is one reason why our example loan above is not going to get a new payment of $335.19, even though that’s what it would be just using the 7.50% increase limitation. The issue is that the first rate adjustment date happens to coincide with the first 60-month recast date. If the example loan didn’t have an initial fixed period of five years—say it was a 3/1 type structure—then the 7.50% payment cap might have come into play after 36 or 48 payments. (Have another drink; we’re not done yet.)

Second, there is a provision to force the loan to amortize whenever the balance hits 110% of the original balance. This is not “scheduled” like the 60-month rolling recast above; it is triggered only for a given loan if and when it has hit the 110% mark, and thus will not necessarily happen on a rate or payment change date; for some loans, it might never happen at all, if the borrower only occasionally makes the minimum payment, or makes a periodic curtailment that brings the balance down. If it does happen, the loan must become a fully amortizing loan—no more minimum payment allowed, all payments must be sufficient to pay all interest due and sufficient principal to amortize the loan over the remaining term. The percent of original balance limitation, in other words, marks the day that neg am is no longer an option for the borrower, and the loan has to start paying down principal from here on out—the borrower is “caught up,” and never again allowed to “get behind.” In our example above, the loan hit the 110% limit after the application of payment 57. So even though this loan was not scheduled for a rate increase or rolling recast until month 60, the servicer would have sent notice to the borrower that as of payment 58, the required payment is the fully-amortizing payment. Note that the loan remains an ARM, even though it is now no longer a neg am ARM. That means that the borrower’s payment can still increase or decrease at future rate change dates. It will simply be, from here on out, an increase or decrease from one fully-amortizing payment to a new fully-amortizing payment.

Neg am ARMs are structured such that the minimum payment will always satisfy at least some interest due. This is true because with a neg am loan, like any mortgage loan, payments are applied to interest before principal. I have noticed that this confuses a lot of people, undoubtedly because we all tend to think in terms of “regular” amortization, which assumes that some portion of a loan payment always goes to principal, and so people imagine that the “principal portion” of the scheduled payment could be larger than the minimum payment, which would result in no cash interest paid in a month. That cannot, however, happen. It doesn’t matter what the “scheduled principal” part of a payment might be; if the borrower’s minimum payment isn’t enough to satisfy both scheduled principal and accrued interest, the payment is applied to the interest, the unpaid interest amount is added to the balance, and no “scheduled” principal reduction occurs. (Compare that to an interest only loan, where the full interest amount is paid by the borrower in cash, but no principal, so the loan balance neither increases nor decreases.) To a borrower in hock, that’s probably a distinction without a difference, but for accounting and regulatory purposes, it’s important (see below under “noncash income” to the lender).

Has your head exploded yet?

But that’s the real point, isn’t it? If your head just exploded, and you’re the kind of person who usually reads CR, just imagine what the kind of person who doesn’t usually read CR makes of all this during some ten-minute spiel by some loan officer. We already know that there are lots of loan officers and brokers who don’t understand how these loans work; remember Babs the Wonder Broker? (One of MaxedOutMama’s finds: someone who is apparently a mortgage Account Executive who was convinced that neg am loans do not charge interest on interest. The only way that could happen is if the required payment each month were calculated only on the original balance, not the original balance plus prior shortfalls. That would, if you did it that way, leave a portion of the total loan balance that isn’t accruing interest. Of course, even if you did that during the neg am period of the loan, once you got to the 60-month recast or the 110% balance cap, you would use the total balance to recalculate the payment, and so from that point forward you would be charging interest on the capitalized interest. That’s not how these loans actually work, but the point is that even if they did work that way you couldn’t consider the capitalized balance to be “free money,” just slightly cheaper money.) So imagine some poor consumer getting “the explanation” from a loan officer who doesn’t understand how neg am works. You’d think that most adults, generally, would be suspicious if they were told by some joker on the internet (say) that banks will actually lend you money without charging interest on it. But if a broker tells you that? They must know, right?

A few more points: the issue of lenders counting negative amortization as interest income keeps coming up in the comments. I hope this example above shows why they do that: it is, actually, interest earned by the lender. It’s just interest that has not yet been paid by the borrower, which makes it “noncash” interest income. It is therefore only as “good as” the collectability of the loan as a whole. Some of us believe that as a loan negatively amortizes, its “collectability as a whole,” as a matter of probability, goes down. Some of us further believe that there are lenders out there who don’t seem to agree, and who therefore under-reserve for these loans (that is, they consider the $99,000 balance just as collectable as the original $90,000 balance, without taking into account that the more the borrower owes, the higher marginal odds of default are, and that a borrower who is making minimum payments might be doing so because the full payment is simply unaffordable).

Also, this discussion I hope makes clear that the “rate shock” issues on neg am ARMs are different from the same issue on a fully-amortizing ARM. As I said earlier, neg am ARMs are by definition a way to “smooth out” rate changes by keeping them from “shocking” the payment. Certainly, not every neg am ARM out there has a five-year initial fixed period, as my example does, or such a deep “teaser” (1.95% vs. 6.50%). Any loan with more potential rate movement in the early years of the loan can negatively amortize faster or slower than my example. We simply need to bear in mind that what is in store for a lot of these loans is the recast shock, and that that shock doesn’t necessarily happen on a scheduled rate change date. The real bad news, friends, is that these things can start blowing up more or less any time, given enough early negative amortization to start kicking in the balance caps. And yes, there are loans out there with 115% caps rather than 110% caps. So it’s incredibly difficult to project out “shocks” on these loans considered as a total portfolio, because they’re not really a homogeneous portfolio when it comes down to details like initial fixed period, depth of initial discount, rate caps, balance caps, etc. Even if they were, one would have to keep modeling “recast shock” predictions based on the actual amount of negative amortization going on, since neg am is a function of what the borrower decides to pay each month. Some of us (OK, me) are worried that the “models” aren’t being “updated” to reflect the actual amount of neg am piling up out there, or that if they are, the lenders aren’t sharing that information with the rest of us.

Last, there’s this question just raised in the comments about why or whether a lender wouldn’t just refinance these neg am borrowers into a new loan, to start the teaser rate thing all over again. Well, they could and they did when house prices were busy rising. The reason it’s a problem now is that the loan originated at a 90% LTV may now have a 99% LTV. To refinance that borrower into another neg am loan is to risk the LTV becoming 109%. I suggested at one point a while ago that a good way to think of a neg am ARM is this: a borrower makes a down payment (neg ams are usually limited to no more than 90% LTV), and then borrows it back, a little bit a month, to subsidize the monthly payment. It’s a mini monthly cash out. That can continue only as long as there is down payment to keep putting down and then slowly borrowing back, and those who refinanced a balance-capped Option ARM to a new Option ARM in the height of the boom were doing so by using that vapor-equity as the new down payment. Once that’s off the table, there’s nowhere to go with these loans except eventual amortization.

Tanta

*In this example, the initial minimum payment is simply fixed for five years. It isn’t actually recalculated every month at 1.95% instead of 6.50%. If it were, the minimum payment would increase slightly every month, because it would be calculated on a slightly higher balance every month (as the actual accrual payment is). I did it this way because many neg am loans work with this “fixed payment” thing. That’s how borrowers get confused into thinking the 1.95% is a fixed rate (when it’s really just a fixed payment “rate”). You could structure the loan such that the minimum payment is actually calculated each month at 1.95%; that would slow the negative amortization slightly by increasing the minimum payment slightly.