With the Libor-rigging scandal still fresh in our memories, pay gaps widening, and the current furor raging over the merits and fairness of high-frequency trading, it’s no surprise that the capital markets have something of a perception problem among the general public. One way to address an incorrect perception is to present a reasonable person with irrefutable evidence, backed up by data. And in the financial markets, when someone presents a new strategy, believes they can make money from a new line of business, or that investing in a new dataset will yield monetary returns, the most convincing way to win your case is through data.
However, that data must be reliable, whereas one reason why rogue individuals at some of the top investment banks could rig the Libor benchmark was simply that the data wasn’t reliable. They could submit rates that were advantageous to them, rather than being accurate, because the rates are a subjective evaluation that differs from bank to bank. And for any over-the-counter dataset that involves any subjective determination, be it a bond or derivative price, a rating, or an estimate, the risk of manipulation is always present. In most cases, any manipulation presents a greater risk of disadvantage—not to mention reputational risk. The same challenges of collecting and aggregating contributed data exist for all these assets, though.
These challenges usually revolve around how firms get a price from a trader’s head or spreadsheet to the rest of their team, to other users firm-wide, and to external clients. This has long been the domain of specialists like Arcontech and Gissing Software—now part of Thomson Reuters, though some of the Gissing crew regrouped as MDX Technology, which has just rolled out its MDXT Connect platform at ING, so the bank can get bond prices from its trading system and dealing desk to sales traders in its offices worldwide.
Meanwhile, Arcontech has a plan to help the industry add a layer of security to benchmark rate distribution, by using its multi-vendor contribution system as a vendor-neutral middleman between data from central banks—such as prices, interest-rate and policy decisions—and vendors that redistribute the data, potentially opening up central banks to broader distribution opportunities, and making their data available without creating any monopoly-like distribution arrangements.
And speaking of contributions, let’s thank companies making a different form of contribution: At this year’s Inside Market Data and Inside Reference Data Awards on May 21, we presented our very first Above & Beyond Award, which isn’t about who produces the best content or builds the best infrastructure, but which rewards those who use their position and expertise to make a difference for others.
This year, the award deservedly went to Markit for its work with St. Baldrick’s, a charity that funds research into cures for childhood cancers, which affect 175,000 children in the US every year, but which receive only four percent of federal cancer research funds. Markit is helping to make up some of that shortfall with a $345,000 donation to St. Baldrick’s this year as a result of its company-wide sponsored head-shaving, which has raised a total of more than $2.2 million in the eight years that the company has run the event, making it one of only two companies to raise more than $2 million for the charity.
Meanwhile, to celebrate the World Cup kickoff, New York-based trading infrastructure provider Perseus Telecom is also making a contribution to a greater good by donating a percentage of revenue from deals signed to its LiquidPath Brazilian connectivity service to AmericaScores, a soccer-coaching charity for kids.
With “banker-bashing” an increasingly popular pastime, these efforts are important not just for the material impact they have on children’s lives, but because they make a broader difference to local communities beyond the financial community, and potentially go some way towards restoring consumer confidence in the industry’s commitment to fix human problems, not just benchmark rates.
Jesse Lund talks about real uses for DLT in the capital markets, lessons learned while rolling out IBM's blockchain platform, and what’s ahead for 2018, and into 2019.Subscribe to Weekly Wrap emails