SMR Research Corporation Stuart A. Feldstein, President

Transcription

1 Mortgage Refinance And Home Equity Loan Propensity Scores Identifying Who's Most Likely To Get A New Loan In The Next Three Months SMR Research Corporation Stuart A. Feldstein, President 300 Valentine Street Hackettstown, NJ Phone Fax Visit Page 1

2 SMR's Scoring Programs For Loan Marketing & Other Uses When the home loan credit crisis began in 2007, most lenders ceased direct marketing of mortgage refinances and home equity loans. Today, delinquency rates are beginning to fall and newly underwritten loans are proving to be safe and profitable. That leaves two questions: 1. Who really wants a new loan? 2. Who qualifies to get one? SMR has designed numerical scoring systems that forecast the likelihood that a specific household will actually obtain a closed loan over the next few months. By modeling against an outcome of people who actually get closed loans, our scores address both of the questions, above. Our higher-scored names and addresses will be the people most likely to qualify for a loan and most likely to want one. We re-score more than 35 million owner-occupied properties every 30 days. We revise our scoring algorithms on a regular basis as well, to reflect current market conditions. This paper will describe the scores we offer, and their effectiveness. Page 2

3 Four Scores SMR produces four scores each entirely different with updated programs, every 30 days. They are: Likelihood to get a home equity loan or line of credit. Our most successful score, this one skews toward the best credits and largest borrowers. Even clients who used this score to find customers in Florida have had a good credit experience, along with excellent loan closing rates on the respondents. Likelihood to get a conventional mortgage refinance. This score was modeled against actual closed-loan customers for conventional mortgage refis not FHA loans. Higher-scored prospects can be at least three times more likely to get a refi than other home owners. Likelihood to get an FHA refinance. FHA will refinance two basic customer groups: Those with existing FHA loans, and those with conventional mortgages who now need or prefer FHA financing. Borrowers whose existing mortgage debt exceeds FHA refi loan limits get zero or very low scores. Only the best get the high scores. Likelihood to get a cashout refinance. Well, there aren't many of these being originated lately. But we still look at those that do get one, and model based on their characteristics. Page 3

4 How The Scores Work Unlike credit scores, the SMR scores are linear easy to understand. In each of our scoring systems, we set a score of 1,000 as the national average likelihood that someone will get a loan in the next few months. Someone with a score of 500 would be only half as likely as the norm to get the loan. Someone with a score of 2,000 would be twice as likely as the norm to get the loan. We don't put an upper limit on the scores. The score is whatever our variables tell us it should be for a given household. We have some folks with scores of 6,000 or higher extremely likely to get a loan. Plenty of others score 500 or lower. Low-scored people often have loan-to-value or other problems, and we don't recommend them. Page 4

5 Scoring Methods Each of the four scores is derived from a multiple regression statistical model. The scores have been tested repeatedly revised and retested frequently since We create the scores using variables from our national property database, which covers a large majority of the USA. Each record in the database is an owner-occupied home with dozens of facts and figures on each of them. Our vendor for raw property data, and for mortgage and home equity loan information, is the nation's largest. They also supply us with AVM (automated valuation model) estimates of current home values, on a "best of five" basis. That is, we get the best of five competing AVM brands, based on which one has been proven most accurate over time in a given county. The AVM values, combined with amortized estimated remaining balances owed on current loans, allow us to create world-class CLTV ratios (combined loan-to-value, meaning total mortgage debt as a percent of home market value). In turn, the CLTVs allow us to understand whether under-water status will defeat a loan applicant. It's one of many variables we use in scoring. Because the database spans most homes and most loans, we are able to see (with almost no margin for error) the answers to lots of questions that plague loan marketing. For instance: 1. If someone has an existing home equity loan, is he more or less likely than the norm to get another one (refinancing the current loan)? 2. If a person's current loan was obtained from a subprime lender of the past, is he more or less likely to refinance or get a home equity loan today? Page 5

6 Scoring Methods (continued) 3. Is there a way to figure out which home owners would benefit by refinancing? What's the current rate? (We either have that or a good way to estimate it.) 4. Is there a relationship between likelihood to get a loan and how long someone has lived in their current home? What's the mathematical difference as each day passes? 5. Is there a geographical difference in the popularity of home equity loans or refis? 6. Who's most or least likely to get a loan: people in singlefamily homes, condos, owned apartments, duplexes, or mobile homes? 7. If the home owner currently has a 15-year mortgage, is he more or less likely than the norm to get a refinance? We use these variables and others in combination in our models to create numeric scores that summarize the overall net likelihood that someone will get a new loan. Page 6

7 Zero-Debt Home Owners: Our Latest Scoring Development When you look at recent net chargeoff results, it's no wonder many lenders have backed away from marketing. What's causing the high chargeoff rates? Several things, but prime among them is the CLTV ratio. People whose debts are high relative to today's reduced home values are going down for the count frequently. So how about targeting home owners who have no mortgage or home equity debt whatsoever? About one-third of all U.S. home owners own their homes free and clear of debt. Yet, they do have cash needs from time to time. For home equity lenders, these are the folks who apply and whose loans turn out to occupy the senior lien position, simply because they have no other loans. SMR has created new scoring algorithms applicable solely to debt-free home owners. We know who they are and we know which ones are most likely to want a loan. They can get a home equity line or they can get a full-fledged mortgage refinance. In either case: 1. They'll likely qualify on a CLTV basis, since they have no debt. 2. They are the least likely to default, according to numerous SMR foreclosure studies. 3. There are plenty of them but only some who really want a loan and will qualify on an income basis which is why scoring is needed. If you like the strategy, just keep this in mind: There's no use sending millions of offers to debt-free home owners who don't need or want a loan. Our scores help pick the best prospects. Page 7

8 Scoring Results The correlation between SMR scores and likelihood to get a loan is quite strong. The next chart shows an example. We randomly selected a group of 1.02 million home owners in nearly all geographies. After applying our scores, we looked at which people in the test file actually got a home equity loan over the next few months. In the chart, we show the 1.02 million home owners sorted into 100 equal-sized groups, based on their SMR scores. Then, we chart the percentage of each group that actually got a new home equity loan. SMR's Home Equity Model in 100 Groups 3.0% % Of Group That Got A Loan In 3 Months 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% 0 1,000 2,000 3,000 4,000 5,000 HE Score Page 8

9 A Customer Case Study Nearly every lender client who has used the SMR scores has come back for more. We have a high level of customer satisfaction. One of the nation's largest thrift institutions is one of them. Their story: It was during the housing boom that this thrift first learned about the SMR scores. Their home equity lending department was looking to boost results in a multi-state region. One of those states was Florida before the crash! The thrift got good results with the scores and began using them for quarterly mailings. Loan growth accelerated. Then came the home price crash. It impacted nearly all Florida lenders. But the impact was very mild for our thrift client. Our scores, it seems, had selected not only people who wanted new home equity loans, but the best credits as well. The thrift continued during the crisis to use SMR's scores. It still uses them today. Growth + safety has been a winning combination. Page 9

10 Score Pricing & More Information The cost of SMR-scored names and addresses depends on four things: 1) The volume of scored names you want. 2) The score range you select (obviously, we sell the most valuable names for a somewhat high price). 3) Additional "selects" such as AVM values, real or estimated current interest rate, etc. 4) Whether you need scores matched to a list you already have (match and append work costs more than buying a list we provide). To discuss a test mailing or to learn more, you can SMR President Stu Feldstein: Stuart.Feldstein@SMRresearch.com, or SMR Modeling Director Jon Varone: Jonathan.Varone@SMRresearch.com Or call us: Page 10