By: Kari Michel
Lenders want to find new customer through more informed credit risk decisions and use new types of data relationships to cross-sell. The strategic goals of any company are to get more customers and revenue while reducing costs on the operating side and the credit loss side. Some of the ways to meet these goals are to improve operating efficiency in creating and managing credit attributes, which represent the building blocks of how lenders make customer decisions.
Lenders face many challenges in leveraging data from multiple credit and non-credit sources (e.g. credit bureaus) and maintaining data attributes across multiple systems. Furthermore, a lack of access to raw data makes it difficult to create effective, predictive attributes. Simply managing the discrepancies between specifications and code can become a very time consuming effort. Maintaining a common set of attributes used in many types of scorecards and decision types often becomes difficult. As a result, there is a heavy reliance on external people and technical resources to find the right tools to try and pull the data sources and attributes together.
In an ideal situation, a lender should be able to easily access raw data elements across multiple sources and aggregate the data into meaningful attributes. Experian can offer these capabilities through its Attribute Toolbox product, allowing one or more systems to access a common set of standard analytics. A set of highly predictive attributes, Premier Attributes, are available and offers a much more effective solution for managing standard attributes across an enterprise. With the use of these tools, lenders can decrease maintenance costs by quickly integrating data and analytics into existing business architecture to make profitable decisions.
