The Review published a piece quoting our CEO:
by Paul Bryant
In 2018, it feels like the use of artificial intelligence (AI) is poised to accelerate unhindered. CB Insights reports that funding deals to AI start-ups increased from 150 in 2012 ($559m invested) to 698 in 2016 ($4.8bn invested). In June 2017, McKinsey ranked financial services first in ‘future AI demand trajectory’ – measured by the estimated percentage change in AI spending over the next three years.
Hedge funds are embracing AI, but wide adoption is unlikelyIn the world of hedge funds, AI is nothing new. According to David Andre, who has a PhD in AI and is CEO of Cerebellum Capital in San Francisco: “[In the past] it has mostly been about fitting models to data … what’s really changed recently are new machine learning (ML) algorithms, such as deep learning, and the improvements in computer power.”
New York-based Rebellion Research, a hedge fund that launched in 2007, has been applying these new techniques. In the early days of the fund, when analysing the Australian economy, its systems automatically adjusted for the rapidly increasing importance of, and correlation with, Chinese industrial output. CEO Alexander Fleiss says: “[Today,] ML not only learns how the economy adjusts for things like commodity prices going up and down; its factors for rating individual assets change over time. So not only will its predictions be different [due to changes in inputs like prices], but the factors that create the prediction will be very different.”
AI complements fundamental research for asset managersCardiff-based technology firm Amplyfi is attacking this space. Algorithms access and analyse both the ‘surface web’ and the ‘deep web’. The surface web is smaller and accessible using standard search engines. The deep web has more information in richer datasets such as academic journals, government databases and financial records. It is less accessible and a vast, relatively untapped resource.
An Amplyfi example
Should researchers and analysts be worried? Probably not. The acid test for many AI techniques used by hedge funds and asset managers will be the ability to demonstrate performance over longer periods and under different market conditions. Andrew Lo, Professor of Finance at MIT Sloan School of Management, in his ‘adaptive markets’ theory, has argued that investment strategies must change over time as markets are neither efficient nor inefficient but ‘adaptive’ and go through periods where the degree of efficiency varies.
AI threatens significant disruption for financial advisers New York-based Pefin claims to be an AI financial adviser at “1/20th the cost” of a human adviser. The platform went live in October 2017 after running in beta with 4,000 users since early 2017. Pefin automates client-adviser interaction, asset allocation and investment decisions.
Should financial advisers be worried? ProbablyShould financial advisers be worried? Probably. Pefin has its own direct-to-consumer offering but also has fast-track growth opportunities such as white labelling – where an incumbent advisory firm would pay to use Pefin’s technology but rebrand the offering as its own.