Exo Investing Blog

Will the next generation of fund managers & advisors be data scientists?


Lennart Asshoff, the CEO of Exo Investing, examines the rapidly changing nature of investment-related technology, in an exclusive article for What Investment.

Spotify, Netflix and Amazon: the last decade has erupted with tech companies leading the charge in the move from face-to-face to digital. Take this one step further and you can see technology surpassing human capabilities entirely. The use of data and artificial intelligence has enabled robots to cut out tumours, to create original novels and to recreate Van Gogh’s brush strokes.

Now we are at a tipping point in financial services: The move towards digital platforms has accelerated exponentially over the last 5 or so years; it feels like there are new robo-advisors being created almost weekly. Whilst some will be built based on fund manager expertise, more and more rely on algorithmic approaches programmed by data scientists.

Plus, news like last week’s article in the FT where Larry Fink, CEO of BlackRock, is quoted to have “thrown his lot in with the machines”, continues to add gravitas to the changing investment landscape, with a significant move towards machines rather than humans. Fink had just reduced the number of fund managers and shifted billions of dollars to a small division of the giant Asset Manager called Systematic Active Equities, a computer-powered “quantitative” investment unit.


The opportunity for data

At Exo, we have partnered with a purely quantitative asset management firm, because we believe in a statistical and analytical approach to investing. We know it’s not possible to predict the future, but, using algorithms that have been honed over 30 years, we are able to utilise the huge amounts of financial data that exists; to build portfolios that give each investor the highest probability of reaching their financial goals.

Antonio Melé, our CTO believes that ‘financial data is a mostly untapped opportunity; never before has there been so much data available to create investor value, such as portfolio personalisation at scale.’

This highly sophisticated quantitative analysis technology behind Exo has previously been available, but only to institutional investors and the very wealthy customers of Private Banks.

Running millions of calculations, minute after minute — has been always been expensive.

However, the advancements in parallel processing, the availability of cloud based support and the development of machine learning has made it possible for us to offer the major benefits and improvement in investment outcomes — including individualised products — to a much wider audience, online, and at the same low price as digital wealth managers.


Humans have limits

Fund management has always existed on the premise of data analysis, however the sheer volume and complexity now required goes so far beyond what a human is capable of. It literally isn’t possible for a human to do thousands of calculations in a split second, and you definitely can’t teach someone to do that — but a machine can.

The time constraint has an additional dimension: While a human could do a very thorough analysis of the market environment, their financial situation, outlook and plans for the future — it would certainly be impossible to do it again the next day, the day after, and the day after that.

Apart from being a daunting task, it would also be a tedious exercise for someone to do. For an automated approach, the repetitiveness is not an obstacle, but instead, with machine learning algorithms teaching themselves how to get better at what they’re doing, it actually represents a strategic advantage.

… and emotions

Emotions and biases get in the way of rational decisions. This presents an additional problem for personal investors and even the most experienced fund managers.

“We’re generally overconfident in our opinions and our impressions and judgments.” — Daniel Kahneman, Nobel Laureate and author of ‘Thinking, Fast and Slow’

And the reality is that, no matter how good you are at your job, this is something you cannot exclude from your investment decision making.

Financial crashes are an extreme example of this but a very relevant one. People can act irrationally, especially during times of crisis. Our algorithms have been built to detect the start of a decline in market performance, and can make the appropriate adjustments, because Exo can review each portfolio, daily. Plus, the machine won’t panic; in fact it eradicates multiple behavioural biases including Loss Aversion or Regret Aversion, which are common stumbling blocks for even the most experienced investors.

The changing landscape

The shift towards a data-driven and tech-focused approach has already begun, and will continue to do so at an exponential rate, which will impact the role fund managers play in the financial planning landscape of the future.

Much like travel agents have not become obsolete across the board and instead there has been a shift to a more specialised approach, I believe the same will be true for fund managers and financial advisers.

There will still be a need for business and family specialists dealing with, for example, complex tax situations, but they will become the exception to the rule.

Man + machine

We see Exo as an example of the powerful combination of man plus machine. We have humans working every day to programme these complex algorithms, and we also give our investors the freedom to focus on specific areas such as Energy, Healthcare and Technology.

In our eyes, Exo uniquely merges technology, investing and risk control, to make individual investing accessible for all -and this has been made possible by us taking a purely data-driven approach. We aim to go “beyond robo” and to accelerate the inevitable paradigm shift in financial services.

Although the launch of Exo to the wider public in April 2018 will be the first time that retail investors will be able to experience such digital individualisation, I have no doubt that this is just the beginning of a significant democratisation of investment through data and technology.

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The views expressed in this exclusive are those of Lennart Asshoff and should not be viewed as investment advice or recommendations; potential investors should always seek the advice of professional investment advisors.

Originally published on WhatInvestment.co.uk