Opening Cross: Utilities Will Get Data Management Out of the Closet… And to the Dry Cleaners

Why duplicate efforts that don't add value?


In fact, it was at APFIC a few years ago that a panel of data professionals clearly enunciated why they so often get stuck with tasks relating to new regulations and compliance requirements, rather than their colleagues in risk management or compliance. The reason, they said, is that regulatory issues are generally data issues, and functions such as reporting and proving compliance are straight-up data issues, where a firm must delve into its databases, capture the correct data points and present them in a usable way. To do this for the plethora of complex regulations out there, firms can’t rely on manual processes—that’s simply too repetitive and time-consuming. What they need is better data governance strategies to ensure data is not just stored, but also properly managed, indexed, cross-referenced, etc., to make it usable. It’s one thing to meet a requirement that data must be stored indefinitely, but quite another that the data should be usable and that you should be able to present specific data points within a set time.

This kind of governance structure isn’t just a requirement for regulatory compliance, though that may have driven most of the spend in these areas over the past few years; it’s also a necessity to be able to leverage Big Data and the kinds of analytics now becoming more commonplace in different areas of the financial markets (see Charles Fiori’s Open Platform elsewhere in this issue). Think of all your data as an enormous collection of clothes in a tiny closet: without a good structure for organizing them, how can you expect to find an item, let alone find the matching sets, or to create a properly coordinated outfit? 

However, there are many aspects of data management that don’t add any competitive advantage, such as basic instrument data management, and cleansing and scrubbing. Think of these as your dry cleaning: it’s inefficient for most people to have a massive dry cleaning machine at home, so we have someone else do it. And the data world is now becoming more open to sending out its cleaning—quite literally—with the emergence of the new Securities Product Reference Data initiative, spearheaded by SmartStream Technologies, Goldman Sachs, JP Morgan and Morgan Stanley. 

For a detailed discussion of SPReD and other utility-related issues, check out the special report on the topic that will be distributed with the November edition of Inside Reference Data. The argument for a utility approach is that a single entity can perform the same role that is currently duplicated across each and every financial firm—all of whom have to ensure clean and accurate instrument data and have to prepare data for regulators—but can leverage economies of scale and eliminate those duplicative efforts and costs. These tasks are non-competitive, and add no revenue stream, so why keep them in-house? The challenge to a utility achieving its aims will be how open data providers are to implementing flexible commercial models to reflect a utility rather than many individual consumers. But either way, firms should still save on the cost of resources.

So in future, regional offices with smaller budgets and staff should be able to take advantage of utilities to focus on other initiatives—either making money from new product development, or saving money through cost management—that do make a difference to their bottom line. 

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