Tag: subprime

By: Kari Michel The topic of strategic default has been a hot topic for the media as far back as 2009 and continues as this problem won’t really go away until home prices climb and stay there. Terry Stockman (not his real name) earns a handsome income, maintains a high credit score and owns several residential properties. They include the Southern California home where he has lived since 2007. Terry is now angling to buy the foreclosed home across the street. What’s so unusual about this? Terry hasn’t made a mortgage payment on his own home for more than six months. With prices now at 2003 levels, his house is worth only about one-half of what he paid for it. Although he isn’t paying his mortgage loan, Terry is current with his other debt payments.   Terry is a strategic defaulter — and he isn’t alone. By the end of 2008, a record  1 in 5 mortgages at least 60 days past due was a strategic default. Since 2008, strategic defaults have fallen below that percentage in every quarter through the second quarter of 2010, the most recent quarter for which figures are available. However, the percentages are still high: 16% in the last quarter of 2009 and 17% in the second quarter of last year. Get more details off of our 2011 Strategic Default Report What does this mean for lenders? Mortgage lenders need to be able to identify strategic defaulters in order to best employ their resources and set different strategies for consumers who have defaulted on their loans. Specifically designed indicators help lenders identify suspected strategic default behavior as early as possible and can be used to prioritize account management or collections workflow queues for better treatment strategies. They also can be used in prospecting and account acquisition strategies to better understand payment behavior prior to extending an offer. Here is a white paper I thought you might find helpful.

A common request for information we receive pertains to shifts in credit score trends. While broader changes in consumer migration are well documented – increases in foreclosure and default have negatively impacted consumer scores for a group of consumers – little analysis exists on the more granular changes between the score tiers. For this blog, I conducted a brief analysis on consumers who held at least one mortgage, and viewed the changes in their score tier distributions over the past three years to see if there was more that could be learned from a closer look. I found the findings to be quite interesting. As you can see by the chart below, the shifts within different VantageScore® credit score tiers shows two major phases. Firstly, the changes from 2007 to 2008 reflect the decline in the number of consumers in VantageScore® credit score tiers B, C, and D, and the increase in the number of consumers in VantageScore® credit score tier F. This is consistent with the housing crisis and economic issues at that time. Also notable at this time is the increase in VantageScore® credit score tier A proportions. Loan origination trends show that lenders continued to supply credit to these consumers in this period, and the increase in number of consumers considered ‘super prime’ grew. The second phase occurs between 2008 and 2010, where there is a period of stabilization for many of the middle-tier consumers, but a dramatic decline in the number of previously-growing super-prime consumers. The chart shows the decline in proportion of this high-scoring tier and the resulting growth of the next highest tier, which inherited many of the downward-shifting consumers. I find this analysis intriguing since it tends to highlight the recent patterns within the super-prime and prime consumer and adds some new perspective to the management of risk across the score ranges, not just the problematic subprime population that has garnered so much attention. As for the true causes of this change – is unemployment, or declining housing prices are to blame? Obviously, a deeper study into the changes at the top of the score range is necessary to assess the true credit risk, but what is clear is that changes are not consistent across the score spectrum and further analyses must consider the uniqueness of each consumer.