Data Management

04:45 PM
Marc J. Firenze
Marc J. Firenze
Commentary
Connect Directly
LinkedIn
RSS
E-Mail
50%
50%

Is Big Data a Problem or an Opportunity?

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.

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
Comment  | 
Print  | 
More Insights
Comments
Threaded  |  Newest First  |  Oldest First
Trendensity
50%
50%
Trendensity,
User Rank: Apprentice
7/29/2014 | 8:33:56 AM
An opportunity with a healthy dose of scepticism
Google's flu data analysis problems illustrated there are no guarantees though this is a huge opportunity for financial services.

Data author Phil Simon also wrote an interesting post about the Oil Metaphor (http://tom.rw/a-closer-look-at-the-data-oil-metaphor-phil-simon-author-of-the-visual-organization/).
HM
50%
50%
HM,
User Rank: Apprentice
7/29/2014 | 4:53:54 PM
HPCC Systems
Marc, I believe Big Data is here to stay. While very few people would hesitate to highlight the value that Big Data represents to organizations and society, the benefits of Big Data are not exempt of risks. The distributed nature of the storage and processing environments of big data engines, such as the HPCC Systems platform, combined with the need for trans-disciplinary collaboration (data analysts, mathematicians, business experts and software developers, all working together) can create situations where certain contents could be exposed, beyond the intention and policies of the organizations. Tokenization, an effective technique while considering standalone datasets, can be trivially reverted given appropriate additional data sources. Moreover, the fact that public cloud environments are sometimes considered, in the course of Big Data implementations, introduces additional risk factors that can be difficult to mitigate. The HPCC Systems platform from LexisNexis Risk Solutions addresses the different risks associated with Big Data and has been using methodologies and techniques for mitigating risk effectively for over a decade. Learn more at http://hpccsystems.com
Greg MacSweeney
50%
50%
Greg MacSweeney,
User Rank: Author
7/30/2014 | 6:58:10 AM
Re: HPCC Systems
Yes, there are many risks with big data, as you point out. Technology vendors have come a long way in securing their hosted and cloud-based offerings, but they certainly have a way to go.
Becca L
50%
50%
Becca L,
User Rank: Author
7/30/2014 | 9:53:22 AM
Re: HPCC Systems
I think we're starting to see a big tipping point in security. Smaller firms were already there to begin with and hadn't really hestitated about cloud security. But a lot of the bigger firms that were very skeptical, and stood on the sidelines of cloud (public and private) have dipped their toes and some have even made the plunge in the last year. The rest of the industry has noted these changes and are increasibgly ready to join in. Tech vendors certainly have more work to do (after all, the security landscape is ever-changing) but FS firms don't need as much convinving as they used to.
Becca L
50%
50%
Becca L,
User Rank: Author
7/30/2014 | 9:55:18 AM
Re: HPCC Systems
I'd also add, big data is so BIG that many firms can't handle what they're taking in. Given the cost vs risk of hosting and managing that on their own, they may have started giving a little less weight to the cloud security concerns.
IvySchmerken
50%
50%
IvySchmerken,
User Rank: Author
7/31/2014 | 12:27:58 PM
Re: HPCC Systems
Blindly collecting data for the sake of participating in the big data trend is not useful and could be costly as well as add risk to the organization. As Marc, points out, data governance is necessary to ensure the data is accurate and is evolving to keep up with changes in stock splits, management and issuers. While firms typically want big data to make better investment decisions or to trade the next hot stock, it can be used in other areas of the business, such as analyzing  trade processing and how many MIPs are needed, say, over the next 12 months. Firms need processes around big data to ensure that it's accurate to rely upon.
Becca L
50%
50%
Becca L,
User Rank: Author
7/30/2014 | 9:48:28 AM
Trendy Tech
Great article, Marc. It's funny how quick firms jump onto these trends without really setting up a plan for how to leverage it. By the same logic, I recently read an article on hiring more Data Scientists for data scientists sake, it leads to as much progress and success as buying tech for tech stake. As you point out, all technology, like new hires, need to be aimed at a problem and trained and tasked to solve it, not just thrown at the data with a prayer for some (or any) results.
More Commentary
SEC Examinations: What to Expect When the SEC Is on It's Way
Theodore Eichenlaub highlights trends in SEC expectations and how to approach a risk assessment of your compliance program.
The Value of Predictive Analytics in Financial Services
Risk management and customer data are two key areas where data analytics is being applied in financial services.
Moving the Trader Closer to the Investment Process
The sell side can demonstrate more value by applying analytics to pre- and post-trading, and by educating buy-side clients about broker segmentation, trading behavior and algorithm shortcomings, and more.
Wirehouses May See More Independent BDs as Retention Packages Expire
Retention bonuses are expiring, leaving brokerages vulnerable to attrition. Is access to technology making it easier for brokers to go independent?
SCI: A Whale of a Regulation
The SEC's Reg SCI weights in at a whopping 742 pages. Here is what you need to know about the oversized regulation.
Register for Wall Street & Technology Newsletters
White Papers
Current Issue
Wall Street & Technology - Elite 8, October 2014
The in-depth profiles of this year's Elite 8 honorees focus on leadership, talent recruitment, big data, analytics, mobile, and more.
Video
5 Things to Look For Before Accepting Terms & Conditions
5 Things to Look For Before Accepting Terms & Conditions
Is your corporate data at risk? Before uploading sensitive information to cloud services be sure to review these terms.