I have only recently returned to WatersTechnology, after a couple of years away covering another beat for our sibling publication, Risk.net. That means I haven’t exactly been keeping abreast of many of the tech changes that have happened to the markets we cover. In some ways, I feel as though I’ve been asleep, and I’m now waking up and coming down from the mountain, like a fintech Rip van Winkle.

Washington Irving’s protagonist returns from his decades-long slumber to find that the American Revolution has occurred and he is now a citizen of the free United States. I missed no revolutions, exactly. Though there have been many in the industries we cover, from cloud computing to artificial intelligence, they were well under way in my time at Inside Reference Data.

These revolutions have in many ways become ‘business as usual’ over these last few years. And some revolutions that were promised have petered out into nothing much at all.

A Flat Circle

In 2015, I was in Singapore covering the annual Sibos conference where the sessions on blockchain were packed out. Distributed ledger was a sexy new tool on the lookout for a use case. In 2019, it’s still on the lookout for a use case—but it’s not so sexy anymore.

Artificial intelligence, however—the science that once sounded like science fiction—has matured into a genuinely exciting new set of disciplines in financial services. AI isn’t new in finance and it’s ubiquitous, but the past few years have seen increasing discussion about techniques that go beyond the commonly used subsets of machine learning and natural language processing. Rarer models, like evolutionary programming, may find new uses as financial institutions look for automation and improved forecasting. 

Imagine going to Walgreens and buying Tylenol tablets. Would you buy Tylenol if there was a one in 10,000 chance there could be a cyanide pill in there? No! Yet in the financial services space, how often are we doing reruns and corrections on the data?

Jonathan Carroll

All of this technological change is set against the backdrop of a world that is changing extraordinarily fast with genuine political revolutions. It’s so common to be acculturated to the accelerating news cycles and hype cycles that to stop and think about how much the planet has altered in the past three years can be dizzying.

We are coming up on the three-year anniversary of the night when I was in a pub in the north London borough of Islington watching on the big screen, along with a load of other anxious Londoners, as Sunderland became the first district in the UK to vote to leave the European Union. Brexit still hasn’t actually happened, but even if it doesn’t, the landscape of finance—and the world at large, for that matter—will never be the same again.

Regulation, too, has undergone major shifts in the past two to three years. In Europe, Mifid II is fully live. The General Data Protection Regulation (GDPR) is a year old and has forced institutions to consider privacy and consent as never before. In the UwS, president Trump’s deregulatory administration has had a go at post-crisis regulations—tailoring or gutting them, depending on which side of the aisle you are on. 

And so I was feeling rather disconcerted when I attended this year’s North American Financial Information Summit (NAFIS). One of our keynote speakers was Jonathan Carroll, chief information officer at the Bank of Montreal. 

Carroll began by asking the delegates why no one really knows their data. Other industries—such as aerospace, or consumer goods—could never operate like that. 

“Imagine going to Walgreens and buying Tylenol tablets. Would you buy Tylenol if there was a one in 10,000 chance there could be a cyanide pill in there? No! Yet in the financial services space, how often are we doing reruns and corrections on the data?” he said.

Carroll’s point was that the capital markets have struggled to achieve the data holy grail: Timely, accurate data flowing across the organisation with clear lineage and governance, sliced in different ways for multiple purposes and multiple geographies, reconciled across the board. 

Immediately, I felt right at home. Carroll could have been speaking in 2016—or indeed, perhaps, in 2006. His message was as timely now as it was then. Good data management is key—and it’s still elusive.

Some things never change.