A new operational model for financial services is being ushered in as the advent of artificial intelligence (AI) begins to take hold among super funds. Incumbent financial institutions, traditionally constrained by a historical reliance on legacy systems and infrastructure, are now able to focus more on the scale and sophistication of their data, opening up new possibilities for how they interact with the fund members of tomorrow.
Where AI most impacts super
Artificial intelligence is transforming the global financial ecosystem. A World Economic forum report last year found that AI is altering the attributes necessary to build a successful business in financial services. According to the report, the next generation of financial institutions that will emerge in the coming years are going to find their competitive advantage on the scale of their data—as opposed to assets—as well as the tailored experiences and the increasing optimisation of digital connectivity that they will offer. Continuously improving product performance to offer superior customer outcomes will be a core focus among these new entrants to keep clients engaged. This will be a new battle for customer loyalty, as the changing expectations of consumers today will be heightened with the growing possibilities of machine learning. What’s more, legacy business models would increasingly be placed under pressure from new entrants, such as FinTech start-ups, that have been able to adapt to the advent of AI and are built around these new attributes.
One key area that AI is expected to transform is member engagement via mobile channels. By reshaping the customer experience, AI can help personalise digital interactions and provide financial planning advice or spending insights – some of which we are already seeing play out across the retail banking sector today. AI-based virtual assistants—such as CBA’s CEBA in Australia, HSBC’s Amy in Corporate Banking or Bank of America’s Erica—are active today, helping customers check balances, remind them about bills and answer bank-related questions. What this means is that traditional financial services institutions are not shying away from the challenge. And one further area where we will see some of the greatest transformative impacts of AI will be in the domain of robo-advice, particularly when it comes to tailored member outcomes around their retirement futures.
The rise of automated advice solutions
Since 2014, the provision of robo-advice has accelerated rapidly in Australia. Robo-advice offerings today generally operate within the domain of more simple advice topics such as basic risk profiling and investment switching, with the more complex topics escalated to an adviser. However, the growing sophistication of artificial intelligence tools used by super funds and financial institutions could result in the expansion of existing robo-offerings to gradually remove manual processes. These AI-powered solutions will be able to identify, segment and solve a greater breadth of everyday investment issues than ever before and provide tailored advice that is accessible on the go.
The potential for AI in robo-advice is vast when considered through its delivery via mobile and digital platforms, opening it up to a greater pool of retail investors than seen to date. For traditional robo-advice solutions, AI could mean intelligently evaluating all current assets and holdings, assessing this alongside preferences for asset allocation and investment return expectations, but also evaluating the extent to which investment bias has affected past decisions for each individual investor. All of this could be used by a machine to completely customise a client’s solution all the way down to their individual set of circumstances, perspectives and preferences and map that against their past investment rationale and financial outlook moving forward.
Can a machine provide more ethical and timely advice than a human?
Allowing for the broader adoption of artificial intelligence in new and compelling ways, robo-advice technology can mean a very large structural shift in terms of the costs of the supply chain of advice. Yet there are real ethical concerns that must be considered.
While speed of delivery is significantly reduced from hours to mere minutes, customers have time and again shown a natural preference for face-to-face advice. Examining the rise of AI in other industries (such as autonomous vehicles) suggests that it’s not always clear whether a machine can make the right decision that acts in “the best interests of a client”. Doing so within financial advice requires empathy for a client’s situation, assessing their priorities and ensuring they meet their goals, as well as understanding when a client may not be honestly offering up all the particulars regarding their financial situation – all of which requires the knowledge and assurance that comes with a human financial planner. Rather than competing with robo-advisors, human financial advisors can leverage AI to improve their efficiency by providing rapid access to tailored investment portfolios and enhance their overall interaction with a client.
Heightened customer expectations, automated experiences, newly wrought data alliances and a transformation of back-office operations all point to the universal disruptive challenge that artificial intelligence represents for traditional industry and retail super funds. As industry incumbents look to adapt, the future looks promising for the next generation coming through that have truly embraced AI and have sought to use it as their compelling point of difference.