Michael Shashoua: Before and After NAFIS

michael-shashoua
Michael Shashoua, editor, Inside Reference Data

Points made at the annual New York-hosted North American Financial Information Summit illustrate how blockchain and data science can or should pivot to better serve data management operations. Michael considers what legal entity identifier efforts could gain from mirroring the approach of these methods.

Before the North American Financial Information Summit (NAFIS) last month, blockchain had already been on the minds of data management professionals. They look at the fragmented nature of its distributed-ledger technology, knowing that there are already plenty of reconciliation issues in reference data, and wonder how to contend with new hurdles to standardization and consistency.

NAFIS sessions explored data governance, regulatory compliance, managed services and the adoption of the legal entity identifier. Data science was addressed as an area that may not be correctly understood and should be more closely examined.

Yet it may be blockchain that is on the top of data managers’ minds. An informal survey of NAFIS attendees in the reference data stream sessions found that they see blockchain as the most likely disruptor for their operations in the next 10 years. Still, any application of blockchain’s distributed-ledger technology—corporate actions processing is already seeing this—will by its nature decentralize information.

Chris Vickery, managing director and chief operations officer at Nomura, argues that blockchain makes it possible to get a “single version of the truth,” and that the decentralization aspect is merely allowing “multiple editing points and multiple owners of the figures.”

Properly Appreciating Science

NAFIS attendees in the reference data stream see blockchain as the most likely disruptor for their operations in the next 10 years.

Another buzzword that parallels blockchain is “data science.” Afsheen Afshar, chief data science officer at JP Morgan Chase, sought to dispel some myths about data science in his remarks to NAFIS attendees. “The elephant in the room about data science is that it’s 90 percent data and 10 percent science, especially in financial services,” he said. To carry out typical data science goals such as increasing revenue, decreasing costs, minimizing risk, and improving management of human capital, firms should map data in service of an actionable insight derived from data science, according to Afshar.

He says “data-as-a-service” (DaaS) is the answer, which means harnessing and leveraging the “data estate”—information about where data is, what it means, and who owns it. Perhaps this approach should be applied to distributed-ledger technology if it catches on for reference data applications.

DaaS is geared toward answering human questions about a business issue. The question being asked has to be targeted, make sense, and be leading toward a purpose. As Afshar put it, “at least 10 times in my career, someone senior has asked me, ‘Can’t we mine LinkedIn data?’ What you should say to that is: To do what? Why? What business problem are we trying to solve?” 

If data science is pursued correctly, and the industry doesn’t revert to managing data the way it always has, then the sought-after goals Afshar identified can be achieved.

Trying to Boost the LEI

Speaking of buzzwords, supporters of the legal entity identifier (LEI) are looking to give the LEI broader reach and significance than it currently has, through increased adoption. The LEI has been solidly implemented, as JP Morgan Chase’s Robin Doyle emphasized during a panel at NAFIS. 

Still, it appears that the obligation to report LEIs is not as strong as it needs to be. According to the Regulatory Oversight Committee that endorses LEI issuers, over 415,000 entities were registered as of the end of January. Last year, Francis Gross of the European Central Bank called the number of LEIs registered (about 338,000 at the time) a “tiny fraction” of what the eventual total should be—and many sources have put the potential figure, or eventual necessary number of registrations, in the millions or multiple millions.

It’s apparent now that what the campaign by LEI adoption supporters needs is to push for a tipping point that creates an exponential jump in the number of registrations (or level of involvement)—just like blockchain and data science have gotten. That will require both strong leadership and greater understanding in the industry as a whole. 

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