What am I? The Truth Behind Legal Entity Data

Remember those children’s books?  A series of simple pictures and clues that describe an animal or an object inevitably leading to a giraffe, a truck, or some other clear answer that a young child can deduce. When it comes to legal entity data, I think industry classifications are very similar, but there are some notable differences. 

As we look ahead, I believe that industry classifications will be one of the top data priorities in the coming years. Industry classifications are those such as NAICS, NACE, GICS, or even the old SIC codes (the last version is from 1987) that we still see a lot of in many legacy systems. While they are based upon clear standards or taxonomies that define what each code means, they still must be assigned by a person, and that’s where the problem lies. Someone has to look at a company, a complex organization that generates tens, hundreds, or billions of dollars, and play a game of “What am I?”

HERE'S AN EXAMPLE

Let’s take The Ford Motor Company. What is Ford? In simple terms, most people would say that Ford is an automobile manufacturer. However, I’ve worked with a major bank who considers Ford a finance company. Rather than look at what Ford commonly does, this institution believes the correct classification of Ford should be based upon the part of Ford’s business that generates the most risk. For this bank, that answer is lending based upon Ford’s extensive credit business.  

Let’s do another one. Pick any National Association bank in the United States. Clearly they’re a banking institution, but are all banks created equal? What if they generate most of their income from mortgages, or consumer loans, or commercial loans, or even credit cards? As we speak with Risk departments and even operations groups that are working to deliver that next generation “enterprise data management," they too are being asked to provide more useful and reliable industry classifications. 

I always try to look as far out as I can to guide our data strategy. On industry classifications, the eventual answer will come from collecting and categorizing every source of revenue coming into a company and not selecting one or two industry classifications, but by providing more granular classification based upon that revenue. I think that with today’s cognitive and big data capabilities, we are in a better position to do that, but we’re still many years away from that perfect case. In the mean time, my advice is always to seek out those that have dealt with the challenges of industry classifications to date and learn how to think about the problem…because its far more complex than you might think.

Download my presentation on Legal Entity Data.