From the rise of the challenger banks to the emergence of the robo-adviser, rarely has our industry seen so much disruption in such a short space of time.
Of course, technology has been a huge driver behind the ongoing changes in the industry, but we have merely scratched the surface. We are still some distance away from its potential being fully realised.
Take the robo-adviser. Created to bring down costs and open up investment to a whole new audience of customers, robo-advisers use algorithms to assess and ultimately determine a user’s risk profile, suitability and life goals. This information is then used to recommend an investment portfolio. With 130 (and counting) robo-advisers on the market, it’s evident that this model is delivering for a growing audience. But it remains a relatively blunt instrument.
Despite being built on the foundation of technology, the robo-adviser model is remarkably open to human error. The majority require a new user to fill in a questionnaire when they sign up, and the answers to the questions will inform what the algorithm recommends. However, if a user submits incorrect data, omits some details, or is simply not asked about a particular aspect of their finances, the algorithm could deliver a misdiagnosed recommendation.
For example, Sarah wants to start investing. She’s been reading some articles online and thinks that a robo-adviser could be a cost-effective way to get started.
She’s not wrong. But what her ISA robo-adviser can’t see and what Sarah doesn’t tell it is that she also has £5,000 of credit card debt and a high-interest loan on her car.
Any human adviser would tell her that paying off her debt is a far more effective use of her savings. But with access to a very limited set of information, her robo-adviser can’t make that judgement call.
Realising the robo-adviser’s potential
Ultimately, robo-advisers aren’t yet making the most of the tools at their disposal. Since the launch of Open Banking over a year ago it’s possible to access a much wider view of a customer’s finances- something that some financial advisers are already making use of.
Robo-advisers have the clear potential to offer truly holistic advice, but manual data entries and fact-finding are often failing to unearth the required information. By using open banking APIs to legally aggregate a customer’s data, the algorithms could access a much wider data set that includes credit cards, bank accounts and the wealth of information this provides and use it to generate far more accurate and effective personalised advice and recommendations – while saving customers from spending hours on fact finding.
And this doesn’t have to end after signing up. By constantly having all the financial data available on the user, advisers and robo-advisers can continue to offer guidance, support and nudges to help the customer maximise their unique circumstances in relation to their investment returns and their money more generally.
Ultimately, we as an industry should always be looking for ways to improve the suitability of financial recommendations. Algorithms can go some way to facilitating this conversation – but surely gaining a better understanding of your customers’ data is the real answer, hidden in plain sight. As any adviser will tell you, more information equals better advice.