Algorithms have made it easier to analyse the stock market and deliver financial advice. As a result, they are now being used to predict investors’ behaviour in order to reduce emotional bias and generate higher returns, according to GlobalData Financial Services.
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By GlobalDataNew technologies have been disrupting the financial industry for some time, and this trend is yet to reach its tipping point. Now new developments in behavioural science have started to enter the wealth management space backed by technological solutions.
Behavioural finance uses social, cognitive and emotional factors to understand the economic decisions of investors. For example, Barclays Wealth and Investment Management has set up a fully dedicated team of specialists in behavioral finance, while IBM developed an analytics tool targeted to financial advisors.
According to our 2016 Global Wealth Managers Survey, only 45.6% of competitors are using or plan to use big data analytics to better understand their clients. However, this proportion is much higher in some markets, and we expect it to increase on a wider scale. Wealth management firms are starting to partner up with technology providers to track customers’ decisions in real-time, which can help avoid the emotional bias that can influence investors.
Cognitive computing and big data are providing valuable insight into client behaviour by analysing social media and spending patterns. In this way, wealth managers will have a greater understanding of their clients’ personalities and attitudes towards risk, and will be able to design their investment strategies accordingly. The findings will also provide material for managers to explain to clients the cost of their emotions and help coach them through turbulent times.
Ultimately, big data can prevent unnecessary losses due to panic selling. These technologies should also come in handy when matching advisors to clients, as similar personalities are more likely to work together effectively.
The main challenge will be assessing when it is best to moderate investors’ emotions and when it is best to adapt to them. Advisors should be aware of their own behavioural biases, which most of the time equally affect investment strategies.
Financial planning is highly emotional when an investor’s expectations about future lifestyle achievements come into play. Wealth managers should keep in mind clients’ buying attitudes before deciding solely on the basis of investment profitability. And no matter how accurate behavioural analysis software becomes, data provided by social media can be as biased as client behaviours. Individuals tend to paint a different picture of themselves on social media platforms, putting forward the highlights of their experiences rather than their real life.
Yet these challenges can to some extent be addressed by goal-based strategies. Advisors should not undervalue the opportunities provided by big data and behavioural analytics. Combined they will help wealth managers deliver a more personalised service and link investment strategies to the broader personality and lifestyle of the client. The benefits of big data are already being explored by banks such as Lloyds Banking Group and Citibank in their retail operations.
Wealth managers that are able to successfully implement similar technology will gain a significant competitive advantage over other players.
