This blog post is part of a 5-part series. It was originally published on December 15, 2016 and updated on July 17, 2019.
Businesses 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 began utilizing trended data in its Desktop Underwriter® (DU®) platform in 2016. 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.
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 three 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.
Learn more about Equifax Trended Data Solutions. Also, check out our other articles in this series: