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.