The temptation for many advisory firms has been to tinker at the edges with some investment in technology in order to be part of the sector’s digital transformation or to play catch-up. However, understanding where to invest and how could be as simple as observing your family, neighbours, friends and colleagues. That’s because current and changing consumer behaviours provide valuable insight into how the world of financial advice needs to adapt to remain competitive and to survive.
By this I mean that our lives today are underpinned by technology and machine learning. They are not only enhancing our experiences but they are changing the way we consume products, listen to music, communicate with others, pay for goods and services, manage our household expenditure, determine where we cut back our spending or make investments.
Slowly our houses and our lives are integrating machine learning devices; from the Nest thermostat that is monitoring your every move to determine patterns, Facebook that shows you the latest cycling accessory based on your hobbies, Alexa/Siri/Cortana waiting patiently for the next command to the fitbit capturing your every step and sleep patterns, we are cocooned in devices that make the daily grind that little bit better. New fridges will soon be on the market that, when they identify a food item such as fish, they will deliver a recipe or cooking suggestion while upstairs a robo-assistant irons and folds the laundry. Many of these inventions are designed to solve problems that we didn’t realise existed before; now we’re unable to cope without them.
Map this to financial advice. With consumers increasingly demanding technology that does the heavy lifting, why is financial advice so different? At the end of the day the problem isn’t necessarily where to buy the ISA or which pension provider to select, it goes deeper. It’s the consumer’s out-of-control spending habits, their fears about being able to afford the future, confusion and embarrassment about retirement, how they will afford their dream home or provide their children with a deposit on a flat or money for university…. the list goes on depending on their age and circumstance. Collating this information and offering up a bespoke solution is what consumers will increasingly demand as digital solutions across the rest of their daily life solve irritating problems.
But in a sector where we are already suffering from a shortfall in adviser numbers and increasing pressures to service more and more clients, the indulgence of really getting to know a customer in this way sounds expensive and time consuming.
For inspiration, we need to look at how other brands are using machine learning to enhance the life of our customer while also driving their business forward. Names such as Amazon, Facebook, Apple and Google are becoming indispensable – it’s hard to imagine a world without them. They are skilled at getting under the skin of their consumers because of their access to enormous amounts of data that consumers readily share with them; photos, text, videos, browsing habits and locations – a myriad of data that allows them to tailor product offerings.
Once confined to the corner office, data is the future and without doubt it’s the future of the financial advisory sector. It is the most valuable currency in an age where machine learning algorithms learn and optimise their operations to improve performance developing ‘intelligence’ over time. Only by understanding the real financial wellbeing of our customers through data can we create the roboadviser of the future. This is a key reason whyOpen Banking is one of the most significant developments in the financial sector for decades. The opportunity to create modern, client-centred solutions as a result of sharing data is a break-through. We can expect personal financial management tools where the financial planning AI – with unrestricted access to all financial data – considers a client’s entire personal financial situation; how they manage their money, their savings and spending habits, their behaviours and so on. The tools will be able to consider alternative ‘what if’ scenarios in real time and recommend changes for improving their financial wellness. This will take the user experience to the next level and increase the value of the services offered to users.
Combine financial advice powered by machine learning with our customers’ existing comfort level with products such as Alexa and Siri and this takes you to the next level. You are looking at the potential for consumers to rely on their virtual personal assistant for an update on their financial situation and potentially managing their money, assets and debts based on their situation – which of course Alexa will be up-to-date on having spent a considerable amount ordering Christmas food, drink presents and an expensive winter skiing holiday.
And this takes us back to trust and comfort levels. While it’s hard to image that Facebook or Amazon could provide financial advice, their global smart-connected digital consumer platforms are just one step away because of three reasons; they understand the consumer better than anyone; the consumer trusts them with vast amounts of personal information; and finally, they are spending $billions on AI research and investment.
However, offering financial advice is a complex web of regulation and specialisation. For the tech giants and disruptors to enter the advice field, they’re going to need to know what they’re doing. And this is where the advice firms have the advantage. We’re already the experts in delivering financial advice. What we need to do now is hone our understanding of the customer. However, to do this quickly, we have to embrace the fact that machine learning might be able to do this better than us – and that an augmented human adviser plus digital approach, whether in reality or virtually, is going to be the solution.
The AI-augmented human adviser will be able to handle a much larger number of cases and will spend more time on engagement and growth. They will be exposed to and practicing the interesting and challenging parts of the advice journey improving their skills at a faster rate. From a customer perspective, their interactions with human advisers will be much softer, while also being more accurate and far faster. The customer will spend most of their time talking about their dreams and goals, their needs, their wants, their fears while the hard facts will be collected by an AI-powered robo-planner authorised by the customer to collect all of the pertinent details from one of the data aggregators. Another benefit of the hybrid approach is the reassurance that human interaction can provide. Altus research clearly demonstrates that customers desire to be able to contact a human via phone or webchat either during or after they have made the decision to invest in a digital roboadviser – is important to 80% of customers.
The roboadvice industry is already pushing the boundaries. For example, the Wealth Wizards AI Guild is currently working on the next generation of advice powered by Turo, our new AI capability that provides access to faster cutting-edge roboadvice for the entirety of the advisory sector. This work includes state-of-the art features such as voice, chat, emotive bots and computer vision capabilities that could be a reality in the near future.
According to Don Scuerman, CTO of Pegasystems, ‘the best chess player in the world is not a human or a computer; it’s a human and computer playing together.’ The same will be true of advice. Financial advisers will work with machine learning to complement their own skills and knowledge in order to offer a new style of service to a transformed customer – this must be the norm if firms are to survive and thrive.
This article originally appeared in Global Banking and Finance Review