Telecommunications, Cable & Utilities

-- by Dan Buell Towards the end of 2007, the management of Bay Area Credit Service embarked on an agressive strategy to dramatically enhance the company's market position and increase its collection revenues.  These goals could be achieved only through superior performance at competitive rates.  At the same time, though, the company needed to drastically reduce internal operating expenses while facing significant competition.  The company's major goals for 208 included: *  Earn a much larger share of business from one of the nation's top five cellular phone service providers; *  Become a major collections partner for one of the nation's largest banking institutions; *  Earn more than 50 percent of the market in the pre-charge-off, early-out segment for the nation's largest landline communications provider; *  Enhance the company's position in the secondary collections tier. It's an interesting case study.  Navigate to the link to learn more: https://www.experian.com/whitepapers/index.html

Optimization is a very broad and commonly used term today and the exact interpretation is typically driven by one's industry experience and exposure to modern analytical tools. Webster defines optimize as: "to make as perfect, effective or functional as possible". In the risk/collections world, when we want to optimize our strategies as perfect as technology will allow us, we need to turn to advanced mathematical engineering. More than just scoring and behavioral trending, the most powerful optimization tools leverage all available data and consider business constraints in addition to behavioral propensities for collections efficiency and collections management. A good example of how this can be leveraged in collections is with letter strategies. The cost of mailing letters is often a significant portion of the collections operational budget. After the initial letter required by the Fair Debt Collection Practice Act (FDCPA) has been sent, the question immediately becomes: “What is the best use of lettering dollars to maximize return?” With optimization technology we can leverage historical response data while also considering factors such as the cost of each letter, performance of each letter variation and departmental budget constraints, while weighing the alternatives to determine the best possible action to take for each individual customer. n short, cutting edge mathematical optimization technology answers the question: "Where is the point of diminishing return between collections treatment effectiveness and efficiency / cost?"