Does "data enrichment" mean combining data from different sources or splitting it in unique ways?

If you look at most of the transactions on a bank statement in the U.S., it's a bunch of gibberish with random letters and numbers. Some of this makes more sense than others, but it's not very clean.

What enrichment does is, clean up all of the random numbers and digits that a consumer is not going to recognize or care most of the time and then show, for example, an actual name of the merchant—Walmart or Amazon instead—with a logo, and to create a better user experience when you're looking through the list of transactions, to help people recognize their transactions. That's an example of enrichment—taking data and just making it better and more usable for the end user. 

Another would be to run some machine learning or just a heuristic algorithm to figure out “What are the recurring subscriptions?” because your bank cannot tell you what your subscriptions are, because it's just one transaction after another. 

But these enrichment players, they can look at it. Plaid also does that now. It's like they are bundling in more and more of these services, going deeper and deeper into the value chain. There are enrichment companies who can help you look at that data and tell you “Hey! What are recurring subscriptions?” And then, they can go even deeper, “What's this person's annual income? What's our prediction of their annual income? What's our prediction of their creditworthiness based on the cash flow that we're seeing for them? In the case of a company, let's estimate the cash flow and balance sheet.”