Much has been made about the proliferation of data, particularly as it relates to an increase in the amount that is required to meet regulatory obligations. While it’s easy to make the case that this increase in mandatory data generation and retention is a cost that is imposed upon a business and one that has a negative impact on profitability, a more enlightened examination of the matter reveals that this proliferation of data actually represents an opportunity to gain insight, expand activities and improve profitability across the enterprise. The good news is that by completing the deed of fulfilling your regulatory obligations you can pave the way to meet multiple needs down the road.
Step One: Meet RNLD
Just as you can’t build a skyscraper without first setting up a strong foundation, job one for managing data is making sure the data that is both created and retained is of the highest quality. This is easier said than done, particularly with an enterprise that has been up and running for some time. There are new tools/technologies that exist that look across existing systems to pull data into a common container. This is commonly called a ‘data lake’ or ‘enterprise data store’ and the goal is to bring all data into a common container.
Regardless of the container, the core step is building out a reconciled, normalized lifecycle database, or RNLD. Just like the equity industry’s CAT (consolidated audit trail) , it is important to try and build a RNLD across asset classes and geographies for your own business. The ultimate goal is to feed it with reconciled data between your version of the events and the different market centers. The RNLD becomes the foundation on which you can maintain consistency, auditability and repeatability.
Next: Pairing Market and Lifecycle Data
Step two is no small feat: pairing market data with lifecycle data. To begin with, the choice of market data sourcing is critical. Whether going directly to the source or to the myriad market data vendors that offer a normalized feed, great care should be taken to understand if the data source being tapped is a good match or fit with the task at hand. In order to get the most out of your data, you need sufficient resolution in the data and you need to confirm that it is time stamped consistently and accurately. While you want to get as granular as possible, the ultimate goal is to pick an approach and stick with it. In general, the more granular you can go consistently, the more needs you can fill going forward.
Outcome: Virtually Limitless Opportunities
Once you have performed this 2-part deed, a world of opportunities presents itself. From surveillance to reporting to alpha generation to transaction cost analysis (TCA) to financial risk management, there are many applications that can be built. You can gain a huge advantage over your competition and dramatically shorten your time to market on new apps if you build out this infrastructure correctly. On top of the existing apps you can build, you can start generating multiple alternative data sets with this capability, leading to even greater possibilities. If, however, you get it wrong, the expression ‘garbage in, garbage out’ is just the beginning of your problems. This becomes a huge resource drain and regulatory, reputational and every other type of ‘R’ risk you can throw out there will increase.
And that’s just the beginning
Getting a firm grasp on the current state of the state with your data and then building a foundation on which you can move forward are just the tip of the iceberg when it comes to making the most of your data infrastructure. The amount of information that is available both in your existing data and alternate data sources that you can pair it with is virtually limitless and the tools that are available to extract, transform and leverage data have exploded in recent years. It truly is a whole new world when it comes to the value of data and Eventus has some further thoughts to share on making the most of things.
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