By: Wendy Greenawalt
The US has the most extensive credit bureau data in the world. The available credit data is vast and very complex making it difficult to synthesize the data across bureaus. Transforming tri-bureau data into informed decisions is challenging for most financial institutions. Due to this, many organizations rely on a highly skilled team of credit data experts to create and manage their credit attributes.
Creating or modifying tri-bureau credit attributes requires extensive credit data knowledge. It’s similar to making a cake. Everyone knows it takes certain ingredients to bake a cake but if the measurements are not precise then the cake will not taste good and may even be flat in the middle. Similarly, not knowing all the nuances to bureau data can produce inaccurate results. For an organization to accurately develop tri-bureau attributes, it requires years of analyzing available bureau data, creating attribute definitions and testing the attributes to validate them for accuracy.
This data expertise already exists within the credit bureaus and can easily be leveraged to ensure that the underlying data is accurately evaluated across all bureaus. Data intelligence can assist organizations in interpretation, translation, and manipulation of bureau data, helping them utilize the information to make smarter and more informed decisions. Examples of data intelligence can include tri-bureau attribute leveling, creation of custom attributes, system migrations and auditing of scorecards and/or attributes to validate analytical accuracy. In my next blog I will discuss the specific challenges lenders face when creating tri-bureau and custom attributes.