Like robo-advisory, AI in wealth management will be another chance for digital leaders to pull ahead of the competition

This week I’m joining world famous ‘hacker’ and author Kevin Mitnick on a panel at the Cyber Incursion conference in London to share ideas about AI and threat intelligence. In cybersecurity, vendors of AI technology have a receptive audience. Threats and attacks are multiplying, while the systems and architecture administrators need to protect are evolving and scaling faster than ever. System administrators are human, and they need all the help they can get. AI tech is sold on the basis of efficient automation, sifting the signal from the noise, and freeing up valuable expert time: and that’s all good. For IT teams, technology is their native element, so it makes sense when someone offers more technology to make their life easier.

But what about the benefits of AI for the rest of the business? While IT administrators and infosec professionals understand what problems they are trying to solve and how AI might help, in the wider context of business operations and servicing customers, it’s a lot harder to see how to take advantage if processes, tools, services, and skillsets are not already highly digital.

When we work with wealth management firms and private banks in the UK, we see this effect: everybody is well aware that AI is set to bring the industry a new wave of software capabilities, but isn’t this yet more technology that is going to take budget away from the core business, potentially disrupt smooth operations for staff and customers, and generally confuse everyone with only a very uncertain path to value?

All these objections certainly could be true if the business is not careful. Technology advisors need to help business leadership to approach AI not with hype, and not with silver bullets, but from the point of view of solving specific problems, in particular where a system is already mostly or fully digital, and therefore can be boosted by AI capabilities.

Robo-advisory provides a proof of concept for sceptics

With the recent rise of robo-advisory services in wealth management, business leadership have had a good view of how to benefit from specific use cases in improving automation, efficiencies, and scalability via software and intelligent use of data.

Many established advisory and stockbroking firms became aware of robo-advisory approaches because of an influx of would-be disruptors: the fintechs of mass consumer investment such as Nutmeg, Scalable Capital, and eToro. But these newcomers are probably better understood as a source of design inspiration instead of as direct competitors for the wealth management activities of the established firms (so far at least).

The positive outcome has been to break down resistance to automation. Many in the industry are recognising the competitive opportunity robo-advisory represents if exploited proactively: good news for a sector that on the whole has been slower than retail banking to commit to digital transformation.

Our clients are implementing digital investment services, including fully mobile self-service portals, which keep their existing customers engaged and help them attract thousands of new investors – something previously unthinkable in the context of manual, paper processes. The trick is how to migrate the customer experience over from those pre-digital systems fast enough and with a reliable outcome – an area where we collaborate closely with customers in each project.

Helping humans work smarter

A well-implemented robo-advisory service empowers a wealth manager’s end customers to do more with their money, getting access to more sophisticated and high performing investments, in more personalised and engaging ways, with better compliance and risk management, and with less delays and costs caused by unnecessary interactions with support and personal advisors.

Relationship managers and financial advisors are still doing what they are good at, but they are working smarter thanks to having better tools and understanding of their customers – who in turn become more informed and engaged. Finally, the analysts and asset managers are seeing their strategies scale up and benefit more people more accurately. In other words, this is a story of AI helping the humans work together better, quite the opposite of the robots taking over.

Disruption risk for digital laggards

On the other hand, there are laggards, for whom ‘automation’ and ‘efficiency’ are interpreted negatively as euphemisms for job cuts and gutting the human expertise from the business. There are too many wealth management firms which have been slow to accept how digitalisation could be positive for them, struggle with partial or neglected digital services, and still rely heavily on paperwork and face to face meetings. Unfortunately, investors’ ideas about the service they expect to see have shifted very rapidly and these firms are seeing their clients drain away to more agile competitors, particularly the younger generations within wealthy families.

The wider range of technologies and software enhancements referred to collectively as AI hold the same promise and risk as the specific example of robo-advisory wealth services. The faster moving financial institutions who can upgrade systems to exploit AI are going to reap the rewards, while the laggards who are stuck in previous generations of technology or only partially digital operations will not be able to access any of these benefits.

AI prospects for digital wealth management

Ultimately I am optimistic that the wealth management and private banking sectors will be able to exploit AI well, because behind the scenes, investment managers and strategists are all highly literate in statistics and understand the advantages of being smarter and faster in the use of data. All that’s needed is a strategy towards digitalisation that is open to exploiting the expertise and technology of partners, and collaborating to identify and prioritise improvements that most directly make a difference to customer experience and value.

This strategy, whether it’s about AI or any other trending buzzword such as cloud or blockchain, is about knowing where you want to go, and using the technology to get there faster. This cannot be achieved by reactively chasing every new software sales pitch, and it won’t help to try to change everything all at once in a totalitarian digital great leap forward. By looking at continuous, incremental improvements it will be clear where AI and other digital improvements can make a big difference, and it will be easier to deploy it, realise the value, and keep on improving.

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