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of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy text ever since the 1500s, when an unknown printer took a galley of type and scrambled it to make a type specimen book. It has survived not only five centuries, but also the leap into electronic typesetting, remaining essentially unchanged. It was popularised in the 1960s with the release of Letraset sheets containing Lorem Ipsum passages, and more recently with desktop publishing software like Aldus PageMaker including versions of Lorem Ipsum
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Since 2007, when the housing and credit crises started to unfold, we’ve seen unemployment rates continue to rise (9.7% in March 2010 *) with very few indicators that they will return to levels that indicate a healthy economy any time soon. I’ve also found myself reading about the hardship and challenge that people are facing in today’s economy, and the question of creditworthiness keeps coming into my mind, especially as it relates to employment, or the lack thereof, by a consumer. Specifically, I can’t help but sense that there is a segment of the unemployed that will soon possess a better risk profile than someone who has remained employed throughout this crisis. In times of consistent economic performance, the static state does not create the broad range of unique circumstances that comes when sharp growth or decline occurs. For instance, the occurrence of strategic default is one circumstance where the capacity to pay has not been harmed, but the borrower defaults on the commitment anyway. Strategic defaults are rare in a stable market. In contrast, many unemployed individuals who have encountered unfortunate circumstances and are now out of work may have repayment issues today, but do possess highly desirable character traits (willingness to pay) that enhance their long-term desirability as a borrower. Although the use of credit score trends, credit risk modeling and credit attributes are essential in assessing the risk within these different borrowers, I think new risk models and lending policies will need to adjust to account for the growing number of individuals who might be exceptions to current policies. Will character start to account for more than a steady job? Perhaps. This change in lending policy, may in turn, allow lenders to uncover new and untapped opportunities for growth in segments they wouldn’t traditionally serve. * Source: US Department of Labor. http://www.bls.gov/bls/unemployment.htm

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.

By: Wendy Greenawalt Optimization has become somewhat of a buzzword lately being used to solve all sorts of problems. This got me thinking about what optimizing decisions really means to me? In pondering the question, I decided to start at the beginning and really think about what optimization really stands for. For me, it is an unbiased mathematical way to determine the most advantageous solution to a problem given all the options and variables. At its simplest form, optimization is a tool, which synthesizes data and can be applied to everyday problems such as determining the best route to take when running errands. Everyone is pressed for time these days and finding a few extra minutes or dollars left in our bank account at the end of the month is appealing. The first step to determine my ideal route was to identify the different route options, including toll-roads, factoring the total miles driven, travel time and cost associated with each option. In addition, I incorporated limitations such as required stops, avoid main street, don’t visit the grocery store before lunch and must be back home as quickly as possible. Optimization is a way to take all of these limitations and objectives and simultaneously compare all possible combinations and outcomes to determine the ideal option to maximize a goal, which in this case was to be home as quickly as possible. While this is by its nature a very simple example, optimizing decisions can be applied to home and business in very imaginative and effective means. Business is catching on and optimization is finding its way into more and more businesses to save time and money, which will provide a competitive advantage. I encourage all of you to think about optimization in a new way and explore the opportunities where it can be applied to provide improvements over business-as-usual as well as to improve your quality of life.
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