How to Get an Ulcer from Differentiated Decisions and Attribution
A recent American Banker article, “New Credit Data Joins Mainstream,” addressed determining the credit worthiness of consumers outside the “superprime” category. In doing so, it defined the gulch between policy management and Risk IT/Operations.
For credit policy, adding second data sources is a slam dunk. A small increase in variable cost gives a much clearer picture. We highlighted this when we talked about multiple models for risk decisioning. Neither FICO, Beacon, Advanced Wireless, nor Telco 98, gives you the full view for the best decisions. The bottom line is that attributes make policy smarter. Obviously, the question is how to go about making smarter policy a reality. Understanding the value of the data is the beginning. Better data leads to better attribution. For a marketing campaign, being able to get multiple sets of data on a customer means being able to create policies that gate on important characteristics. If someone has travel as an interest, most marketers will start flooding them with offers for sky mile cards. But, do they already have two or three cards? Do they carry a high enough revolving balance for this to be worthwhile? Do they actually have the disposable income to afford vacations? One of the easiest ways to improve offer acceptance is to put gates in your outbound marketing policy to ensure you are marketing intelligently, based on what you could – and should – know about them.
Risk managers see the same benefits from gating attributes. A risk score may not be as predictive with one or two trade lines. Perhaps this triggers getting a bankruptcy score. A lot of activity may mean too much activity, thus showing the need for an income score. This isn’t new theory. Your data and analytic vendors have been telling you this for months and months. Getting analytics operational is essential. Often it’s the most difficult part of creating a successful policy which can be implemented. A 1990’s mainframe data acquisition solution or any other cumbersome legacy technology isn’t agile enough to just “add data.” And often, IT priority has been defined for the foreseeable future.
In contrast, current data integration platforms can add new data in less than three months at a fraction of the cost. In fact, modern data integration platforms pay for themselves with the first change you make. The first time you want a new score or data source (like L2C), you get it done now, you get it done right, and you get it done in a usable manner.
Data acquisition is about more than just getting the data into your system, it’s about integrating it into the decision-making process. Before you make the decision to add data, you likely build some attributes, run regression analysis (or get a team of analysts to do it for you), and build a policy. This won’t come as a surprise to anyone who has tried to add data recently, but bringing the now-validated policy to bear on newly acquired data isn’t as simple as it may look.
In our next blog, we will address exactly how your data acquisition plan falls off the rails.
If you want to talk to an Equifax specialist about attribution, please send us an e-mail.
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