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.  

I received a call on my cell phone the other day. It was my bank calling because a transaction outside of my normal behavior pattern tripped a flag in their fraud models. “Hello!" said the friendly, automated voice, “I’m calling from [bank name] and we need to talk to you about some unusual transaction activity on your account, but before we do, I need to make sure Monica Bellflower has answered the phone. We need to ask you a few questions for security reasons to protect your account. Please hold on a moment.”  At this point, the IVR (Interactive Voice Response) system invoked a Knowledge Based Authentication session that the IVR controlled. The IVR, not a call center representative, asked me the Knowledge Based Authentication questions and confirmed the answers with me. When the session was completed, I had been authenticated, and the friendly, automated voice thanked me before launching into the list of transactions to be reviewed. Only when I questioned the transaction was I transferred, immediately – with no hold time, to a human fraud account management specialist. The entire process was seamless and as smooth as butter. Using IVR technology is not new, but using IVR to control a Knowledge Based Authentication session is one way of controlling operational expenses. An example of this is reducing the number of humans that are required, while increasing the ROI made in both the Knowledge Based Authentication tool and the IVR solution.  From a risk management standpoint, the use of decisioning strategies and fraud models allows for the objective review of a customer’s transactions, while employing fraud best practices. After all, an IVR never hinted at an answer or helped a customer pass Knowledge Based Authentication, and an IVR didn't get hired in a call center for the purpose of committing fraud. These technologies lend themselves well, to fraud alerts and identity theft prevention programs, and also to account management activities. Experian has successfully integrated Knowledge Based Authentication with IVR as part of relationship management and/or risk management solutions.  To learn more, visit the Experian website at: https://www.experian.com/decision-analytics/fraud-detection.html?cat1=fraud-management&cat2=detect-and-reduce-fraud).  Trust me, Knowledge Based Authentication with IVR is only the beginning. However, the rest will have to wait; right now my high-tech, automated refrigerator is calling to tell me I'm out of butter.