Outlook 2017: Tom Doris, OTAS
Tom Doris is CEO of equity-analytics provider OTAS.
Which hot topics/hype should be retired at the end of 2016?
Some of the hype around artificial intelligence (AI) has died down and now we’re seeing more serious and sensible attempts to use the new methods as a tool to deliver real value to the investment process. Getting past the buzz will allow firms to focus on defining what role AI will play and how traders can best work with these technologies.
As we move away from the far-fetched sci-fi ideas, the focus can move to how these technologies can solve specific problems, and just as importantly, to understand where they should not be applied.
The important point is that market data volume and information overload has been one of the main challenges faced by traders for many years, we now have tools that really can provide good solutions to extract the important information, which is a huge breakthrough. But like any new technology, once the hype dies down, there’s a lot of work to be done on the awkward problems of getting the technology into the right platforms, and into the workflow of the users, and feeding into the firms’ audit trails.
What changes do you expect to see in regards to machine learning and analytics in 2017?
As an industry we have been moving towards more of an ecosystem model for the first time. Thinking has evolved with a rapid change in attitude from keeping everything in-house to placing a priority on innovation and collaboration.
Firms want to focus on the work and look towards a collective ecosystem with third-party provider content in their workflows. We are also seeing a democratization of technology across the industry where everything is much more open and standards-based. This creates a more even playing field and opens up access for startups to innovate and deliver scalable solutions. As the regulatory environment changes and firms work to adhere to new requirements, this ecosystem and collaborative approach is even more vital to success. We need to work together to build solutions to fix these problems and create a healthier, even playing field.
Making the distinction between artificial intelligence and machine learning.
eFinancialCareers reports that low-vol markets favor man over machine.
After successful tests in Europe, the bank expects a fourth quarter rollout.
Firms should first crawl and then walk before they run with AI.
It no longer economical to throw bodies at problems.