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By: Wendy Greenawalt On any given day, US credit bureaus contain consumer trade data on approximately four billion trades. Interpreting data and defining how to categorize the accounts and build attributes, models and decisioning tools can and does change over time, due to the fact that the data reported to the bureaus by lenders and/or servicers also changes. Over the last few years, new data elements have enabled organizations to create attributes to identify very specific consumer behavior. The challenge for organizations is identifying what reporting changes have occurred and the value that the new consumer data can bring to decisioning. For example, a new reporting standard was introduced nearly a decade ago which enabled lenders to report if a trade was secured by money or real property. Before the change, lenders would report the accounts as secured trades making it nearly impossible to determine if the account was a home equity line of credit or a secured credit card. Since then, lender reporting practices have changed and, now, reports clearly state that home equity lines of credit are secured by property making it much easier to delineate the two types of accounts from one another. By taking advantage of the most current credit bureau account data, lenders can create attributes to capture new account types. They can also capture information (such as: past due amounts; utilization; closed accounts and derogatory information including foreclosure; charge-off and/or collection data) to make informed decisions across the customer life cycle.

Vintage analysis 101 The title of this edition, ‘The risk within the risk’ is a testament to the amount of information that can be gleaned from an assessment of the performances of vintage analysis pools. Vintage analysis pools offer numerous perspectives of risk. They allow for a deep appreciation of the effects of loan maturation, and can also point toward the impact of external factors, such as changes in real estate prices, origination standards, and other macroeconomic factors, by highlighting measurable differences in vintage to vintage performance. What is a vintage pool? By the Experian definition, vintage pools are created by taking a sample of all consumers who originated loans in a specific period, perhaps a certain quarter, and tracking the performance of the same consumers and loans through the life of each loan. Vintage pools can be analyzed for various characteristics, but three of the most relevant are: * Vintage delinquency, which allows for an understanding of the repayment trends within each pool; * Payoff trends, which reflect the pace at which pools are being repaid; and * Charge-off curves, which provide insights into the charge-off rates of each pool. The credit grade of each borrower within a vintage pool is extremely important in understanding the vintage characteristics over time, and credit scores are based on the status of the borrower just before the new loan was originated. This process ensures that the new loan origination and the performance of the specific loan do not influence the borrower’s credit score. By using this method of pooling and scoring, each vintage segment contains the same group of loans over time – allowing for a valid comparison of vintage pools and the characteristics found within. Once vintage pools have been defined and created, the possibilities for this data are numerous… Read more about our analysis opportunities for vintage analysis and our recent findings on vintage analysis.

— by Jeff BernsteinSo, here I am with my first contribution to Experian Decision Analytics’ collections blog, and what I am discussing has practically nothing to do with analytics. But, it has everything to do with managing the opportunities to positively impact collections results and leveraging your investment in analytics and strategies, beginning with the most important weapon in your arsenal – collectors.Yes, I know it’s a bit unconventional for a solutions and analytics company to talk about something other than models; but the difference between mediocre results and optimization rests with your collectors and your organization’s ability to manage customer interactions.Let’s take a trip down memory lane and reminisce about one of the true landscape changing paradigm shifts in collections in recent memory – the use of skill models to become payment of choice.AT&T Universal Card was one of the first early adopters of a radical new approach towards managing an emerging Gen X debtor population during the early 1990s. Armed with fresh research into what influenced delinquent debtors into paying certain collectors while dogging others, they adopted what we called a “management systems” approach towards collections.They taught their entire collections team a new set of skills models that stressed bridging skills between the collector and the customer, thus allowing the collector to interact in a more collaborative, non-aggressive manner. The new approach enabled collectors to more favorably influence customer behavior, creating payment solutions collaboratively that allowed AT&T to become “payment of choice” when competing with other creditors competing for share of wallet.A new of set of skill metrics, which we now affectionately call our “dashboard,” were created to measure the effective use of the newly taught skill models, and collectors were empowered to own their own performance – and to leverage their team leader for coaching and skills development. Team developers, the new name for front line collection managers, were tasked with spending 40-50% or more of their time on developmental activities, using leadership skills in their coaching and development activities. The game plan was simple.• Engage collectors with customer focused skills that influenced behavior and get paid sooner.• Empower collectors to take on the responsibility for their own development.• Make performance results visible top-to-bottom in the organization to stimulate competitiveness, leveraging our innate desire for recognition. • Make leaders accountable for continuous performance improvement of individuals and teams.It worked. AT&T Universal won the Malcom Baldrige National Quality Award in 1992 for its efforts in “delighting the customer” while driving their delinquencies and charge-offs to superior levels. A new paradigm shift was unleashed and spread like wildfire across the industry, including many of the major credit card issuers and top tier U.S. banks, and large retailers.Why do I bring this little slice of history up in my first blog?I see many banking and financial services companies across the globe struggle with more complex customer situations and harder collections cases — with their attention naturally focused on tools, models, and technologies. As an industry, we are focused on early lifecycle treatment strategy, identifying current, non-delinquent customers who may be at-risk for future default, and triaging them before they become delinquent. Risk-based collections and segmentation is now a hot topic. Outsourcing and leveraging multiple, non-agent based contact channels to reduce the pressures on collection resources is more important than ever. Optimization is getting top billing as the next “thing.”What I don’t hear enough of is how organizations are engaged in improving the skills of collectors, and executing the right management systems approach to the process to extract the best performance possible from our existing resources. In some ways, this may be lost in the chaos of our current economic climate. With all the focus on analytics, segmentation, strategy and technology, the opportunity to improve operational performance through skill building and leadership may have taken a back seat.I’ve seen plenty of examples of organizations who have spent millions on analytical tools and technologies, improving portfolio risk strategy and targeting of the right customers for treatment. I’ve seen the most advanced dialer, IVR, and other contact channel strategies used successfully to obtain the highest right party contact rates and the lowest possible cost. Yet, with all of that focus and investment, I’ve seen these right party contacts mismanaged by collectors who were not provided with the optimal coaching and skills.With the enriched data available for decisioning, coupled with the amazing capabilities we have for real time segmentation, strategy scripting, context-sensitive screens, and rules-based workflow management in our next generation collections systems, we are at a crossroads in the evolution of collections.Let’s not forget some of the “nuts and bolts” that drive operational performance and ensure success.Something old can be something new. Examine your internal processes aimed at producing the best possible skills at all collector levels and ensure that you are not missing the easiest opportunity to improve your results.
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