Big Data Online Summit: Big Data as a Vehicle for Change

Large swaths of information, both structured and unstructured—whether internal, such as email, or external, such as tweets—are neither new to financial firms nor particularly useful on their own, according to participants at the Waters online Big Data Online Summit, which persistently returned to this theme.

A constant challenge for providers in the space is to sort out not just what Big Data is, but how end-users can justify investing in managing it. And that work requires a different, more organizationally focused conception of Big Data, beyond the plain definition—consistent access to and manipulation of real-time data, without further need for bespoke development.

Stuart Grant, business development manager for EMEA at Sybase, says, for example, that while the impetus for Big Data may well be five V's—volume, variety, value, velocity, and visualization—that surround today's market data and news sources, "the key issue is still whether Big Data can provide a revenue source, without making an outsized investment that is either a hot potato or too big to succeed."

That is likely why 60 percent of Big Data uses are installed incrementally, or tactically, according to Grant, and involve market data analytics, intra-day risk assessment, and real-time financials revolving around liquidity and funding. For example, he says, insurance firms are addressing the resource drain of Solvency II by becoming more data-aware. “Meanwhile, financial firms are developing social media and semantic analysis for particular trading desks, and aggregating annual or quarterly reporting with tick information into a single bucket,” Grant adds.

But the trick is for organizations to grow out their data strategy with, to use another “v” word, Big Data as vehicle. Just as cloud is used for "migration,” such as back-testing trading strategies, Big Data can help firms transition to better data governance, move more ownership of data to the front office, and deconstruct silos that were constrained by decades-old limitations on usability. Perhaps more importantly, Big Data can leverage the skills and knowledge trapped in those silos on an enterprise level, says Grant. In fact, with increased reporting requirements, with vast amounts of company activity now required to be stored, it may well be that Big (internal) Data will bear more fruit than the well-treaded feeds of machine-readable news. However, this will require a more strategic, rather than piecemeal, approach.

Whether the Big Data “idea” holds enough currency to persuade firms to strike the delicate balance between tactical and strategic—or clear important organizational hurdles like privacy surrounding internal relationships—remains a puzzle.

Big Data's progression in the so-called financial technology "hype cycle" may be reaching a critical point and, unlike cloud, the concept doesn't quite have the mainstream application—or clever branding of Microsoft or Amazon—to back it. It may never get there, but perhaps it doesn't have to.

Grant describes Sybase's Big Data practice as something of a marriage counselor for financial firms, negotiating paths by which Big Data can be weaved into firms' particular cost-constrained requirements. It seems they can be convinced—but only with an argument evincing subtle understanding of firms’ individual data needs, rather than a simple appeal to “critical mass” surrounding the technology. And that, inevitably, is a more onerous case to make.