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- Test
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In my previous two blogs, I introduced the definition of strategic default and compared and contrasted the population to other types of consumers with mortgage delinquency. I also reviewed a few key characteristics that distinguish strategic defaulters as a distinct population. Although I’ve mentioned that segmenting this group is important, I would like to specifically discuss the value of segmentation as it applies to loan modification programs and the selection of candidates for modification. How should loan modification strategies be differentiated based on this population? By definition, strategic defaulters are more likely to take advantage of loan modification programs. They are committed to making the most personally-lucrative financial decisions, so the opportunity to have their loan modified – extending their ‘free’ occupancy – can be highly appealing. Given the adverse selection issue at play with these consumers, lenders need to design loan modification programs that limit abuse and essentially screen-out strategic defaulters from the population. The objective of lenders when creating loan modification programs should be to identify consumers who show the characteristics of cash-flow managers within our study. These consumers often show similar signs of distress as the strategic defaulters, but differentiate themselves by exhibiting a willingness to pay that the strategic defaulter, by definition, does not. So, how can a lender make this identification? Although these groups share similar characteristics at times, it is recommended that lenders reconsider their loan modification decisioning algorithms, and modify their loan modification offers to screen out strategic defaulters. In fact, they could even develop programs such as equity-sharing arrangements whereby the strategic defaulter could be persuaded to remain committed to the mortgage. In the end, strategic defaulters will not self-identify by showing lower credit score trends, by being a bank credit risk, or having previous bankruptcy scores, so lenders must create processes to identify them among their peers. For more detailed analyses, lenders could also extend the Experian-Oliver Wyman study further, and integrate additional attributes such as current LTV, product type, etc. to expand their segment and identify strategic defaulters within their individual portfolios.

–by Andrew Gulledge General configuration issues Question selection- In addition to choosing questions that generally have a high percentage correct and fraud separation, consider any questions that would clearly not be a fit to your consumer population. Don’t get too trigger-happy, however, or you’ll have a spike in your “failure to generate questions” rate. Number of questions- Many people use three or four out-of-wallet questions in a Knowledge Based Authentication session, but some use more or less than that, based on their business needs. In general, more questions will provide a stricter authentication session, but might detract from the customer experience. They may also create longer handling times in a call center environment. Furthermore, it is harder to generate a lot of questions for some consumers, including thin-file types. Fewer Knowledge Based Authentication questions can be less invasive for the consumer, but limits the fraud detection value of the KBA process. Multiple choice- One advantage of this answer format is that it relies on recognition memory rather than recall memory, which is easier for the consumer. Another advantage is that it generally prevents complications associated with minor numerical errors, typos, date formatting errors and text scrubbing requirements. A disadvantage of multiple-choice, however, is that it can make educated guessing (and potentially gaming) easier for fraudsters. Fill in the blank- This is a good fit for some KBA questions, but less so with others. A simple numeric answer works well with fill in the blank (some small variance can be allowed where appropriate), but longer text strings can present complications. While undoubtedly difficult for a fraudster to guess, for example, most consumers would not know the full, official and (correct spelling) of the name to which they pay their monthly auto payment. Numeric fill in the blank questions are also good candidates for KBA in an IVR environment, where consumers can use their phone’s keypad to enter the answers.

A recent New York Times (1) article outlined the latest release of credit borrowing by the Federal Reserve, indicating that American’s borrowed less for the ninth-straight month in October. Nested within the statistics released by the Federal Reserve were metrics around reduced revolving credit demand and comments about how “Americans are borrowing less as they try to replenish depleted investments.” While this may be true, I tend to believe that macro-level statements are not fully explaining the differences between consumer experiences that influence relationship management choices in the current economic environment. To expand on this, I think a closer look at consumers at opposite ends of the credit risk spectrum tells a very interesting story. In fact, recent bank card usage and delinquency data suggests that there are at least a couple of distinct patterns within the overall trend of reducing revolving credit demand: • First, although it is true that overall revolving credit balances are decreasing, this is a macro-level trend that is not consistent with the detail we see at the consumer level. In fact, despite a reduction of open credit card accounts and overall industry balances, at the consumer-level, individual balances are up – that’s to say that although there are fewer cards out there, those that do have them are carrying higher balances. • Secondly, there are significant differences between the most and least-risky consumers when it comes to changes in balances. For instance, consumers who fall into the least-risky VantageScore® tiers, Tier A and B, show only 12 percent and 4 percent year-over-year balance increases in Q3 2009, respectively. Contrast that to the increase in average balance for VantageScore F consumers, who are the most risky, whose average balances increased more than 28 percent for the same time period. So, although the industry-level trend holds true, the challenges facing the “average” consumer in America are not average at all – they are unique and specific to each consumer and continue to illustrate the challenge in assessing consumers' credit card risk in the current credit environment. 1 http://www.nytimes.com/2009/12/08/business/economy/08econ.html


