Then, on the way to your destination, your phone has already picked up from your messaging conversation that you’re going to a new restaurant with friends – and the Google Assistant, using Google Duplex – has called ahead to book a table for four. Software that’s able to hold a conversation with a staff member over the phone and sound believably human. It’s even checked the restaurant offers vegan and gluten-free options - it knows how particular your fellow diners are.
Then imagine you could use the technology driving these innovations to further your knowledge about certain stocks, which could then give you an advantage over everyone else. That particular technology is AI and machine learning. It’s driving change in a wide range of sectors – and the financial world is no exception.
For those wanting to stay ahead within this field it’s becoming vital that all types of investors leverage services that use AI for segments of their portfolio. In the very near future using tools influenced by machine learning will be commonplace, and not using them would be almost like not having access to a smartphone today.
For example, the team at GAM Systematic have developed proprietary tools to interpret big data sets. This includes tracking weather patterns, shipping data, and even using natural language processing tools to understand how both positive and negative news is affecting stocks. Making sense of this data quickly is key - enabling GAM Systematic to turn overwhelming amounts of information in to something useful and actionable incredibly quickly.
These new types of systems also democratise the world of investing. Trading doesn’t have to just be about hedge funds - big data opens up investment to more people, allowing small-scale investors to have access to information that will enable them to stand alongside those investing billions.
There is one big question surrounding AI and automation – does this make humans obsolete in certain sectors? Anthony Lawler, the Co-Head of GAM Systematic, says that is unlikely, both generally and in the world of finance, because the human touch is crucial. He says: “There is no formula you can write down that will perfectly predict the future of markets and that is very important to always remember. I think we are truly making more informed decisions. Machine learning and data sets don’t give you perfect answers, they just give you more information – and more information is usually better.”
Having said this, there are some benefits to losing a human touch to aspects of the process. Entrusting the examination of data and trends to AI means software can operate detached from unconscious biases - software can look at potential trades removed from personal sentiment about a particular stock. It also avoids recency bias, or the temptation to ‘join the herd’ on shifting trends for fear of missing out on an opportunity. It makes its recommendations based on facts and data, offering a more logical and impartial range of suggestions. The ‘human touch’ then comes next – where an investor can decide how to use that information – this time with a balanced and impartial view of the current trading situation.
As with all large technological shifts a major stumbling block is trust. Whether it’s a self-driving car, or a computer placing a call for you - people are generally afraid of the new, of the unknown. Lawler argues that trust is already being built with AI. We’re becoming used to computer interaction and dealing with systems that are based on this technology – from Netflix’s film recommendations, to the conversations we have with Alexa to order the latest book from Amazon. All operate because machines are amassing and detailing massive data sets that make this process appear natural, and we then trust them over time. Lawler says investment will be no different:
“What we’re seeing in investment management is a natural extension of that comfort with AI in our homes. People are more comfortable that technology can play a beneficial role and is not something scary, or disconnected from the world. It’s a tool that we can use and so I think having part of a portfolio managed by quantitative methods is becoming a much more natural choice.”
Machine learning and AI is ultimately making data more accessible. It’s allowing the wealth of information now available about the world to become manageable for everyone. It’s removing the cognitive load of sifting, sorting and understanding vast amounts of data and allowing people to focus on what they’re best at – bringing experience, understanding and passion to the task at hand. Investors are no different – they want access to more data to make truly informed choices, and AI is enabling that.
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