
In this article…
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Phasellus at nisl nunc. Sed et nunc a erat vestibulum faucibus. Sed fermentum placerat mi aliquet vulputate. In hac habitasse platea dictumst. Maecenas ante dolor, venenatis vitae neque pulvinar, gravida gravida quam. Phasellus tempor rhoncus ante, ac viverra justo scelerisque at. Sed sollicitudin elit vitae est lobortis luctus. Mauris vel ex at metus cursus vestibulum lobortis cursus quam. Donec egestas cursus ex quis molestie. Mauris vel porttitor sapien. Curabitur tempor velit nulla, in tempor enim lacinia vitae. Sed cursus nunc nec auctor aliquam. Morbi fermentum, nisl nec pulvinar dapibus, lectus justo commodo lectus, eu interdum dolor metus et risus. Vivamus bibendum dolor tellus, ut efficitur nibh porttitor nec.
Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Maecenas facilisis pellentesque urna, et porta risus ornare id. Morbi augue sem, finibus quis turpis vitae, lobortis malesuada erat. Nullam vehicula rutrum urna et rutrum. Mauris convallis ac quam eget ornare. Nunc pellentesque risus dapibus nibh auctor tempor. Nulla neque tortor, feugiat in aliquet eget, tempus eget justo. Praesent vehicula aliquet tellus, ac bibendum tortor ullamcorper sit amet. Pellentesque tempus lacus eget aliquet euismod. Nam quis sapien metus. Nam eu interdum orci. Sed consequat, lectus quis interdum placerat, purus leo venenatis mi, ut ullamcorper dui lorem sit amet nunc. Donec semper suscipit quam eu blandit. Sed quis maximus metus. Nullam efficitur efficitur viverra. Curabitur egestas eu arcu in cursus.
H1
H2
H3
H4
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Vestibulum dapibus ullamcorper ex, sed congue massa. Duis at fringilla nisi. Aenean eu nibh vitae quam auctor ultrices. Donec consequat mattis viverra. Morbi sed egestas ante. Vivamus ornare nulla sapien. Integer mollis semper egestas. Cras vehicula erat eu ligula commodo vestibulum. Fusce at pulvinar urna, ut iaculis eros. Pellentesque volutpat leo non dui aliquet, sagittis auctor tellus accumsan. Curabitur nibh mauris, placerat sed pulvinar in, ullamcorper non nunc. Praesent id imperdiet lorem.
H5
Curabitur id purus est. Fusce porttitor tortor ut ante volutpat egestas. Quisque imperdiet lobortis justo, ac vulputate eros imperdiet ut. Phasellus erat urna, pulvinar id turpis sit amet, aliquet dictum metus. Fusce et dapibus ipsum, at lacinia purus. Vestibulum euismod lectus quis ex porta, eget elementum elit fermentum. Sed semper convallis urna, at ultrices nibh euismod eu. Cras ultrices sem quis arcu fermentum viverra. Nullam hendrerit venenatis orci, id dictum leo elementum et. Sed mattis facilisis lectus ac laoreet. Nam a turpis mattis, egestas augue eu, faucibus ex. Integer pulvinar ut risus id auctor. Sed in mauris convallis, interdum mi non, sodales lorem. Praesent dignissim libero ligula, eu mattis nibh convallis a. Nunc pulvinar venenatis leo, ac rhoncus eros euismod sed. Quisque vulputate faucibus elit, vitae varius arcu congue et.
Ut convallis cursus dictum. In hac habitasse platea dictumst. Ut eleifend eget erat vitae tempor. Nam tempus pulvinar dui, ac auctor augue pharetra nec. Sed magna augue, interdum a gravida ac, lacinia quis erat. Pellentesque fermentum in enim at tempor. Proin suscipit, odio ut lobortis semper, est dolor maximus elit, ac fringilla lorem ex eu mauris.
- Phasellus vitae elit et dui fermentum ornare. Vestibulum non odio nec nulla accumsan feugiat nec eu nibh. Cras tincidunt sem sed lacinia mollis. Vivamus augue justo, placerat vel euismod vitae, feugiat at sapien. Maecenas sed blandit dolor. Maecenas vel mauris arcu. Morbi id ligula congue, feugiat nisl nec, vulputate purus. Nunc nec aliquet tortor. Maecenas interdum lectus a hendrerit tristique. Ut sit amet feugiat velit.
- Test
- Yes

By: Wendy Greenawalt In my last blog on optimization we discussed how optimized strategies can improve collection strategies. In this blog, I would like to discuss how optimization can bring value to decisions related to mortgage delinquency/modification. Over the last few years mortgage lenders have seen a sharp increase in the number of mortgage account delinquencies and a dramatic change in consumer mortgage payment trends. Specifically, lenders have seen a shift in consumer willingness from paying their mortgage obligation first, while allowing other debts to go delinquent. This shift in borrower behavior appears unlikely to change anytime soon, and therefore lenders must make smarter account management decisions for mortgage accounts. Adding to this issue, property values continue to decline in many areas and lenders must now identify if a consumer is a strategic defaulter, a candidate for loan modification, or a consumer affected by the economic downturn. Many loans that were modified at the beginning of the mortgage crisis have since become delinquent and have ultimately been foreclosed upon by the lender. Making optimizing decisions related to collection action for mortgage accounts is increasingly complex, but optimization can assist lenders in identifying the ideal consumer collection treatment. This is taking place while lenders considering organizational goals, such as minimizing losses and maximizing internal resources, are retaining the most valuable consumers. Optimizing decisions can assist with these difficult decisions by utilizing a mathematical algorithm that can assess all possible options available and select the ideal consumer decision based on organizational goals and constraints. This technology can be implemented into current optimizing decisioning processes, whether it is in real time or batch processing, and can provide substantial lift in prediction over business as usual techniques.

For the past couple years, the deterioration of the real estate market and the economy as a whole has been widely reported as a national and international crisis. There are several significant events that have contributed to this situation, such as, 401k plans have fallen, homeowners have simply abandoned their now under-valued properties, and the federal government has raced to save the banking and automotive sectors. While the perspective of most is that this is a national decline, this is clearly a situation where the real story is in the details. A closer look reveals that while there are places that have experienced serious real estate and employment issues (California, Florida, Michigan, etc.), there are also areas (Texas) that did not experience the same deterioration in the same manner. Flash forward to November, 2009 – with signs of recovery seemingly beginning to appear on the horizon – there appears to be a great deal of variability between areas that seem poised for recovery and those that are continuing down the slope of decline. Interestingly though, this time the list of usual suspects is changing. In a recent article posted to CNN.com, Julianne Pepitone observes that many cities that were tops in foreclosure a year ago have since shown stabilization, while at the same time, other cities have regressed. A related article outlines a growing list of cities that, not long ago, considered themselves immune from the problems being experienced in other parts of the country. Previous economic success stories are now being identified as economic laggards and experiencing the same pains, but only a year or two later. So – is there a lesson to be taken from this? From a business intelligence perspective, the lesson is generalized reporting information and forecasting capabilities are not going to be successful in managing risk. Risk management and forecasting techniques will need to be developed around specific macro- and micro-economic changes. They will also need to incorporate a number of economic scenarios to properly reflect the range of possible future outcomes about risk management and risk management solutions. Moving forward, it will be vital to understand the differences in unemployment between Dallas and Houston and between regions that rely on automotive manufacturing and those with hi-tech jobs. These differences will directly impact the performance of lenders’ specific footprints, as this year’s “Best Place to Live” according to Money.CNN.com can quickly become next year’s foreclosure capital. ihttp://money.cnn.com/2009/10/28/real_estate/foreclosures_worst_cities/index.htm?postversion=2009102811 iihttp://money.cnn.com/galleries/2009/real_estate/0910/gallery.foreclosures_worst_cities/2.html

By: Wendy Greenawalt Optimization has become a "buzz word" in the financial services marketplace, but some organizations still fail to realize all the possible business applications for optimization. As credit card lenders scramble to comply with the pending credit card legislation, optimization can be a quick and easily implemented solution that fits into current processes to ensure compliance with the new regulations. Optimizing decisions Specifically, lenders will now be under strict guidelines of when an APR can be changed on an existing account, and the specific circumstances under which the account must return to the original terms. Optimization can easily handle these constraints and identify which accounts should be modified based on historical account information and existing organizational policies. APR account changes can require a great deal of internal resources to implement and monitor for on-going performance. Implementing an optimized strategy tree within an existing account management strategy will allow an organization to easily identify consumer level decisions. This can be accomplished while monitoring accounts through on-going batch processing. New delivery options are now available for lenders to receive optimized strategies for decisions related to: Account acquisition Customer management Collections Organizations who are not currently utilizing this technology within their processes should investigate the new delivery options. Recent research suggests optimizing decisions can provide an improvement of 7-to-16 percent over current processes.


