Last week Barchart put on its third annual Fintech Exchange, which had a heavy emphasis on data.
The event in its first two years has provided a refreshing change of pace from the typical conference format. Out were the panels of experts discussing well-worn topics in a well-worn format. It was replaced by fintech entrepreneurs on stage in a theater setting forced to make the case for their firm’s value proposition in a limited amount of time.
This put pressure on these tech leaders to be concise and entertaining to keep the audience’s attention. Most succeeded, though even the jeans, sneakers, suit jacket and three-day stubble look can seem formulaic after a while.
This year’s presenters may not have been as entertaining as in past years, but they had a more daunting task: They had to continue to be fresh and this year the theme was data.
To be fair, synthesizing the mountain of data trading firms must parse on a daily basis, while vital, is a tedious job for technology wonks and much harder to make sound exciting than say, predictive analytics. The term data scientist (new to me) was made popular at this event as well as the distinction between data visualization and data analytics.
The latter was the subject of the event’s keynote address by Tableau CEO Vaidy Krishnan. He explained the “5 Whys” technique used to explore cause-and-effect relationships underlying a particular problem, which was created by Sakichi Toyoda, the founder of Toyota Industries. The goal of the method is to determine the underlying cause of a defect or problem by repeating the question "Why?" Each answer forms the basis of the next question. There is no particular magic to the number “5” noted Krishnan, but the process is how he differentiates data analytics from data visualization and in a broader sense what his firm does. He said data visualization is great at revealing a problem, but it doesn’t answer the why question, just the question. Krishnan concluded as he started, by saying the key in big data management is the ability to ask (and get an answer) for the "why" of your data.
It provides a nice setup for the various data firms presenting during the lighting round. The most significant may have been DataRobot’s Justin Dickerson who spoke on artificial intelligence and machine learning. Dickerson’s presentation was somewhat chilling for the numerous data scientists —which is how he defines himself— in attendance because his firm takes all open source algorithms and puts them together to create thousands of additional algos, offering machines learning data analytics for one price point where it used to require a team of data scientists. Even the fintech space is seeing disintermediation and the efficiency of aggregation threaten jobs.
This year included a diverse group, three women presenters and some institutional focus as both CME Group and CBOE presented in the lightning round.
After all this data crunching from data scientists, the lightning round ended on a simpler note with an outreach to retail. Nadex CEO Tim McDermott pointed out how there had been a reduction in retail trading activity since the 2008 financial crisis and that the electrification of markets has to a great extent taken away the most common entry point for new traders—the floor. McDermott made the case that Nadex and binary options is the new path for neophyte traders to learn about markets. “It is a way for retail to get in the space,” McDermott said, adding that once in and acclimated these retail traders will continue their education and begin to trade more sophisticated products.
This year Fintech Exchange was kicked off the night before with a pre-event cocktail party at the offices of Trading Technologies. The venue space was also expanded to make room for many exhibitors, a larger reception area and a series of fintech roundtables was added to the event.
Many speakers and attendees traveled to the event, which is quickly becoming a staple on the fintech conference circuit.