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Dispelling credit attribute myths, Part 3

Published: October 23, 2009 by Guest Contributor

By: Wendy Greenawalt

In the last installment of my three part series dispelling credit attribute myths, we’ll discuss the myth that the lift achieved by utilizing new attributes is minimal, so it is not worth the effort of evaluating and/or implementing new credit attributes. First, evaluating accuracy and efficiency of credit attributes is hard to measure. Experian data experts are some of the best in the business and, in this edition, we will discuss some of the methods Experian uses to evaluate attribute performance.

When considering any new attributes, the first method we use to validate statistical performance is to complete a statistical head-to-head comparison. This method incorporates the use of KS (Kolmogorov–Smirnov statistic), Gini coefficient, worst-scoring capture rate or odds ratio when comparing two samples. Once completed, we implement an established standard process to measure value from different outcomes in an automated and consistent format. While this process may be time and labor intensive, the reward can be found in the financial savings that can be obtained by identifying the right segments, including:

• Risk models that better identify “bad” accounts and minimizing losses
• Marketing models that improve targeting while maximizing campaign dollars spent
• Collections models that enhance identification of recoverable accounts leading to more recovered dollars with lower fixed costs

Credit attributes
Recently, Experian conducted a similar exercise and found that an improvement of 2-to-22 percent in risk prediction can be achieved through the implementation of new attributes. When these metrics are applied to a portfolio where several hundred bad accounts are now captured, the resulting savings can add up quickly (500 accounts with average loss rate of $3,000 = $1.5M potential savings). These savings over time more than justify the cost of evaluating and implementing new credit attributes.

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Today’s changing economy is directly impacting consumers’ financial behaviors, with some individuals doing well and some showing signs of payment stress. And while these trends may pose challenges to financial institutions, such as how to expand their customer base without taking on additional risk, the right credit attributes can help them drive smarter and more profitable lending decisions. With Experian’s industry-leading credit attributes, organizations can develop precise and explainable acquisition models and strategies. As a result, they can: Expand into new segments: By gaining deeper insights into consumer trends and behaviors, organizations can better assess an individual’s creditworthiness and approve populations who might have been overlooked due to limited or no credit history. Improve the customer experience: Having a wider view of consumer credit behavior and patterns allows organizations to apply the best treatment at the right time based on each consumer’s specific needs. Save time and resources: With an ongoing managed set of base attributes, organizations don’t have to invest significant resources to develop the attributes themselves. Additionally, existing attributes are regularly updated and new attributes are added to keep pace with industry and regulatory changes. Case study: Enhance decision-making and segmentation strategies A large retail credit card issuer was looking to grow their portfolio by identifying and engaging more consumers who met their credit criteria. To do this, they needed to replace their existing custom acquisition model with one that provided a granular view of consumer behavior. By partnering with Experian, the company was able to implement an advanced custom acquisition model powered by our proprietary Trended 3DTM and Premier AttributesSM. Trended 3D analyzes consumers’ behavior patterns over time, while Premier Attributes aggregates and summarizes findings from credit report data, enabling the company to make faster and more strategic lending decisions. Validations of the new model showed up to 10 percent improvement in performance across all segments, helping the company design more effective segmentation strategies, lower their risk exposure and approve more accounts. To learn how Experian can help your organization make the best data-driven decisions, read the full case study or visit us. Download case study Visit us

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