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Will low-cost and simple investment advice from machines boost financial inclusion?
Traditional fund management and its multibillion-pound profits are under threat from low-cost robo-advisors – but their growth could bring new investors into the financial markets.
Robo-advice uses machine learning to give tailored financial advice online. James Dunne, head of digital investing at Santander bank, explains: “A customer has a goal, then we try to learn about their appetite for risk, how much they want to invest and then we recommend funds or products. What would be a two-hour face-to-face meeting can take 20-25 minutes.”
Dunne says robo-advice appeals to the digital generation, which typically satisfies wants and needs online and is often unwilling to spend time or money on face-to-face advice.
Narayan Naik, Professor of Finance at London Business School (LBS), agrees that as robo-advice expands it has significant implications for financial inclusion regardless of age. He also says robo-advice can “disentangle some of the conflicts of interest” that fees and charges can lead to. It may also add to pressure on active fund managers – whose performance versus stock market indices is already being questioned. Professor Naik believes high-end advice will remain. However, companies will implement robo-advice to win a share of this new pie.
Julian Birkinshaw, Professor of Strategy and Entrepreneurship and Academic Director of the Institute of Innovation and Entrepreneurship at LBS, says data-rich Google and Amazon could enter the market and further disrupt the sector. Dunne and Professor Naik agree – though any new entrant would be bound by the same regulation. Dunne says there are 5.5 million people in the UK alone who don’t have access to financial advice as traditional providers have shrunk. This is a sizeable prize for Santander and others to chase.
Professor Birkinshaw asks whether machines will herd everybody down the same investment route. Robo-advice will be based on previous decisions and past market performance, criteria known to have led to poor outcomes for investors as bubbles are created and fortunes lost.
However, Dunne says that the technology can counter the tendency to make impetuous buy-sell decisions: “Through technology, we now have the ability to have a dynamic relationship with the client – so when a Brexit or a Trump happens, we’re able to touch the customer really quickly and say, ‘Don’t make a snap decision, hold’. Before, it would have meant an advisor contacting 100-plus people individually.”
Previous podcast: Gary Hamel and Julian Birkinshaw discuss radical change for big organisations in Dealing with Digital Disruption.
Next podcast: Should your organisation be investing in machine learning technologies?
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