Adventures in Analytics: Firms Push for Better Ways to Look at Unstructured Data

One of the hottest trends in the industry is one that's been around for a while: analytics.

dan-defrancesco2
Dan DeFrancesco, Deputy Editor, Sell-Side Technology

Dan talks about how two recent announcements highlight the capital markets' continued obsession with getting the best analytics possible.

It takes a big man ─ something I currently am, thanks to the holiday-season food baby I'm still carrying around ─ to admit when he's wrong, so I think it's time I ask for your forgiveness. Last week, in the spirit of everyone looking at how they can improve themselves, I rattled off some resolutions I thought the industry should give itself for 2016.

While my column touched on three issues that are sure to draw big headlines throughout 2016 — cyber security, blockchain and swap execution facilities (SEFs) — I missed the boat on an even bigger topic that's bound to continue to crop up throughout the year, and beyond: analytics.

Inflection Point

One of the first indications that analytics had "tipped," so to speak, came at our biggest conference of the year, Waters USA, which was held in early December. Nearly every panel that day at least touched on analytics, regardless of what the designated topic was.

And then, less than two weeks into 2016, two big announcements were made by big players in the industry (Bloomberg and Scotiabank) regarding analytics. The former acquired Netbox Blue to add social media monitoring and governance technology to its enterprise compliance platform, Bloomberg Vault. The latter has started a partnership with Queen's University to create a center for applied research on customers.

While analysis of structured data has always been a staple of the markets, the ability to compile massive, unstructured data sets (big data) has opened up a whole new world of opportunities for firms.

I had the chance to speak with Harald Collet, global head of Bloomberg Vault, and Michael Zerbs, co-head of IT for Scotiabank, about their respective announcements and the future of analytics in general. Both agreed there has been a noticeable shift in the demand for analytics amongst all firms.

Analytics 2.0

Now, before I continue, let me pause here to say that I'm not trying to reinvent the wheel here. Analytics have been around forever. It's no secret firms are interested in analyzing data to make better investments and improve their bottom line.

The difference this time around is the type of analytics being performed. While analysis of structured data has always been a staple of the markets, the ability to compile massive, unstructured data sets (big data) has opened up a whole new world of opportunities for firms.

Bloomberg and Scotiabank's recent decisions, particularly the former, are both examples of this. As Bloomberg's Collet explained to me, it's the next logical step for firms to want to start analyzing all the fancy data that's been collected by the big data platforms they've built over the past few years.

Sports!

Because my comparison of blockchain to Steph Curry was so popular last time (I got one email about it!), I think I'll give it another crack, so here goes.

Tim Duncan is a great example as to the power of analytics.

For my money, Duncan is one of the 10 best basketball players of all time. He has been able to evolve his game so he can continue to make an impact. At 39, he's certainly past the prime of his career, yet he remains a key component of one of the three best teams in the NBA.

As Kawhi Leonard continues to establish himself as one of the best players in the NBA, Duncan has adapted his game to complement him and the rest of the team. Duncan's minutes per game, field goal attempts, points and rebounds have all decreased significantly this year in comparison to his career averages. Yet, the team continues to succeed.

Think of Leonard as big data. He's young, exciting and very good. However, without a solid, consistent veteran on the team like Duncan (analytics), Leonard's ceiling is only so high. The two have a symbiotic relationship, with one excelling his career while the other extends his.

Big data, while nice to have, has a limit to its usefulness if a firm is unable to properly analyze it. Analytics, obviously, are dependent upon collecting data.
And so, just as Duncan looks to win his sixth NBA title this year, analytics, with an assist from big data, will look to make a big splash in 2016.

Food for Thought

  • Here's a shameless plug: My January feature went live this week. I profile Mike Madigan, CTO at Chicago-based prop shop WH Trading. Madigan is fiercely committed to keeping his technology in-house, which made him an interesting person to interview. Head over here to give it a read. I also wrote an opinion piece on the the life of high-frequency traders. You can read that here
  • I'm not trying to say I called it, but I think I called it. David Dawkins spoke to Nasdaq's head of blockchain strategy about what's next for distributed ledger technology. You can read the story here.

Like the column? Hate the column? Let me know via email ([email protected]) or Twitter (@dandefrancesco).

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