Is Big Data a Problem or an Opportunity?
Big data is one of the hottest topics facing the technology community and it is one that financial services firms are considering seriously.
When it comes to data, financial services firms are, as a rule, quite circumspect. They fear cyberattacks, data theft, data loss, security breaches, data privacy, and human error. The result of any of these could end up costing millions, or even billions of dollars. At an extreme, it could even cause an existential crisis.
It is against this backdrop that financial services firms are cautiously examining the impact of the big data trend on their business. However, big data could be looked at as an opportunity rather than a threat. Data is often referred to as "the oil for the information age" -- an analogy that, by and large, stands up to scrutiny. Far from presenting a problem the rewards can be enormous for those able to harness or unlock its potential.
Big data is a broad topic with many definitions and the solutions to big data problems cannot be described by simple Yes or No answers. Rather, it is helpful to describe big data solutions by their ability to address problems across four dimensions (the Four V's): Volume, Velocity, Variety and Veracity. The first two of these, Volume and Velocity, are largely quantitative or infrastructure-based issues, readily addressed by the technology available. You simply need a system big enough and fast enough to capture big data; if not, then the benefits will likely be beyond your grasp.
However, the remaining two, Variety and Veracity, are more qualitative issues. The true value of big data is unlocked if you are able to handle and assimilate lots of different data from many different possible sources and then able to make sense of that data and separate the important from the inconsequential.
Collecting data for data's sake is not going to deliver much, if any, benefit. Rather, it's about having high quality data that's useable. Big data – at least usable big data – is not purely a technology or storage issue, but is one that is reliant on quality data and sound data governance.
In the financial services industry, front office requirements about how to make better investment decisions has typically driven the conversation: how will this help us find the next hot stock to buy; where will the next major market dislocation be?
However, information can be harnessed and used to solve other problems or help drive operational efficiencies elsewhere in the firm. Instrumenting businesses, applications, and infrastructure to gain meaningful insights is another significant form of a big data strategy. Improvements can be made across many dimensions including managing risk, operating more efficiently, or improving the client experience. For example, if you're trying to improve straight-through processing (STP) efficiencies, big data could be used to analyze breakdowns and help you target development efforts towards addressing STP capabilities.
In addition, having an agile data governance operational and technical framework is also crucial when it comes to handling and taking advantage of big data. Data is malleable and it will change over time. To take full advantage, it's important to acknowledge this aspect. A fairly straightforward example has to do with the various geographic regions of the world: Countries aren't static entities. They grow, shrink, and split. Similarly, there's the ever-changing dynamic of corporate actions where the relationship between legal entities and the impact to issuer exposure is constantly changing. Therefore, the process around the capture, validation, and publication of information has to support ongoing change, otherwise data will become stale and obsolete.
The arrival of big data for financial services companies is a real opportunity. However, in order to realize its full potential, you must not view big data as a technological issue and let the technology "hijack" you. Tech for tech's sake will frequently produce as many problems as benefits.
Think first about the business benefits and then apply a creative, thoughtful, and flexible approach to big data. This approach will give you the best chance of not only "striking oil," but, more importantly, being able to realize its many practical uses.
As Chief Technology Officer of Eagle Investment Systems , Marc Firenze drives the software, technology, and architecture decisions across Eagle's investment management suite and ensures that development directly supports the firm's corporate vision. With more than 20 ... View Full Bio
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