Looking for Innovation in the World of Ideas

Michael Shashoua, editor, Inside Reference Data

Wearable sensory technology, and a self-critical approach to methods of managing data are just two elements out there that can keep data operations sharp. Michael examines how these can enhance intuitions about financial data.

This month, let’s look at a technological innovation and a philosophical innovation, both of which in their own way can inspire new ways of thinking about data management. Popular science author and lecturer David Eagleman, whose previous takes on neurological functions have been applicable and useful for data operations, speaking at Teradata’s Partners client conference last month, shared his new technology, Vest (Versatile Extra-Sensory Transducer).

Vest is a vest that one can wear. It was conceived to help hearing-impaired people feel speech, but market indicators can be fed into its array of small vibration motors. The wearer can then choose a green or red button based on the feeling those motors convey. Choosing a button to press based on the stimuli determines whether the stock is bought or sold, Eagleman revealed in his presentation.

This technology and experiment fascinates because it makes so-called “gut feelings” and hunches about the market an actual functional system, not something to be dismissed or laughed at. For institutions dealing with more than just single transactional decisions, Vest can provide a feel for information that would otherwise have to be pulled from stores of reference data, and then processed or interpreted to yield insights. If widely adopted by the industry, Vest would streamline and accelerate reading and understanding of reference data, and increase the accuracy of data processing. Fallible human vision could be complemented by other senses to enhance professionals’ abilities to evaluate financial data.

Telling Right From Wrong

Speaking of human fallibility, the other innovation that can be applied to data management is more about a way of thinking and inquiring about perceptions and how science and technology are perceived—and how scientific and technological efforts are carried out. Pop culture writer Chuck Klosterman has an excellent new book out called But What If We’re Wrong? in which he writes about the likelihood of conventional wisdom on topics such as music, sports and politics eventually changing to the exact opposite of what it is now. His approach to scientific understanding is that the best hypothesis to use to test scientific theories is “one that reflexively accepts its potential wrongness to begin with.”

If widely adopted by the industry, Vest would streamline and accelerate reading and understanding of reference data.

I can’t imagine that regulators would be happy if firms reported their risk with the caveat that the regulators should take the figures with a grain of salt, but the industry has seen plenty of predictions over the past 10 or 20 years that turned out to be wildly inaccurate—the dotcom and housing bubbles are just two that come to mind.

So, when looking at risk data management compliance in particular, keep in mind that any compliance plan—including consideration of relevant regulations such as the Fundamental Review of the Trading Book, Basel III and BCBS 239—ought to have a contingency plan for incorrect assumptions or errors being found in reporting.

Accepting Criteria

If you accept Klosterman’s criteria for a scientific or financial risk hypothesis (he calls it “Klosterman’s Razor,” after Occam’s Razor), you have some newer tools for developing measures to weed out incorrect theories or assessments. These include improved linkages between data sources, more adoption of identifiers and more comprehensive assignment of those identifiers. The industry’s challenge is to use these tools to strengthen risk assessments and stamp out wrong investment hypotheses.

Assuming that the standard practices are wrong might sound like the same sort of “gut feeling” about financial investments and operations that needs much more support—the kind that can be provided by a “smart” vest technology. Klosterman’s idea, applied here, can be taken as a challenge to interrogate data management and governance plans more intensely. In fact, to stay sharp as a data professional, one ought to think about innovations and different ways of thinking. Both Vest and Klosterman’s Razor are worthy subjects. 

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