Businesses continue to face ever-increasing regulations and ever-decreasing margins. Financial services, utilities and communications industries alike are seeking ways to drive more profitable growth while controlling expenses and staying within desired risk thresholds. Today, trended data solutions are helping companies expand their customer universe and improve risk decisioning, delivering positive impact to the bottom line. As more companies see the benefit of solutions incorporating trended data, this analytic tool is becoming mainstream.
The adoption of trended data solutions into the consumer credit market underscores the fact that trended data is becoming more commonplace. In fact, Fannie Mae now utilizes trended data in its Desktop Underwriter® (DU®) platform. This extended view of a consumer’s credit history helps mortgage lenders see not only the point-in-time snapshot of a consumer’s credit score and account status, it shows the most recent two years of a consumer’s payment and balance history. This insight helps drive a more informed lending decision.
Trended data solutions have also entered the credit card, banking and auto lending markets, helping companies improve risk modeling and fine-tune target marketing strategies (like which customers are more likely to respond to your offer and pay back their obligations on time). As trended data becomes more commonplace, many financial institutions are embracing this more robust view of consumer financial behaviors. But just what is trended data?
Simply put, trended data solutions (also called time series, historical or longitudinal data) analyze a set of data over a specific period of time. This helps you identify patterns of past behavior. These behavior patterns can then be used to predict future behavior. The predictive nature of trended data helps strengthen analytics and model development so companies can refine business strategies to more profitably grow their portfolio and better assess risk.
More specifically, in trending financial data, we create attributes, or characteristics of a given behavior (such as the number of trades reported within a 3 month period of time) based on algorithms that detect and measure a consumer’s spending, payment, or related financial behavior over time. These algorithms not only help highlight the trajectory of a consumer’s financial path, but also the duration, intensity and magnitude of change in the consumer’s financial behavior. Companies glean valuable insight by analyzing the direction, velocity and tipping points within the data.
In future posts, we’ll explore a variety of ways companies can (and do) use trended data today. We’ll also explore additional topics related to the many ways trended data is delivered, from raw data and attributes to models and pre-configured solutions. In the meantime, feel free to visit our website to learn more about Equifax Trended Data Solutions.
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