What wealth firms can learn from Spotify and Netflix

Traditional model of showing value to high-net-worth clients has its limits, says white paper

What wealth firms can learn from Spotify and Netflix

With portfolio returns increasingly difficult to come by in today’s financial markets, the pressure is on for firms and advisors to prove their value in other areas of the wealth business. For many, the key has been personalization and customized services; for others, the winning strategy has been to play a numbers game.

But according to Deloitte, the future lies in finding a middle ground – and it all starts with technology.

In a recent white paper titled “The ‘Spotifying’ of wealth advice,” the firm explained that the traditional wealth industry model of focusing on high-net-worth clients and their needs cannot be translated to a broader subset of clients.

“Advisors are busy serving existing clients and are challenged in their ability to scale their services to reach more people,” the paper said. “Leveraging a new, hybrid model of doing business, however, could open the door to possibilities that traditional firms could only dream of.”

The catalyst of the hybrid advice model, Deloitte said, is advice driven by data. Using data, heuristics, and models to automate timely insights for each client, advice can be tailored based on a client’s preferences, past trades, behavioural profile, and more.

So where’s the Spotify connection? It’s in how the company transformed its approach to music streaming: from curation services, the company made the leap to recommendation services.

Wealth managers, Deloitte suggested, should consider taking five pages from the Spotify playbook:

  • Invest in talent to drive data-driven product development;
  • Develop new business models linked to data-driven engagement;
  • Create new digital wealth experiences for clients and advisors by capitalizing on data and algorithms;
  • Recognize the need to build or buy capabilities as needed;
  • Design and get the pilot right before scaling.

“The wealth industry can … start ‘Spotifying’ its own processes to streamline user experiences and create and deliver more engaging, tailored insights at the ideal times to a larger clientele,” Deloitte said.

The data-driven future of wealth advice might not be that far off. Robert Madej, CEO at PureFacts Financial Solutions, told Wealth Professional how data-based insights can unlock new possibilities for the wealth industry.

“Right now, Netflix knows more about most of us than our financial advisor does. That's going to change,” he said. “Our financial advisors are going to learn a lot more about us and by doing so, they're going to be able to service us in a way that makes more sense.”

Most clients working with PureFacts, Madej said, are keen to get integrated access to clients’ data to enable much more powerful data analytics, machine learning, and AI in their businesses. The goal is to serve clients better and show more value for the fees they’re being charged, but to do so in a cost-efficient way.

“That’s certainly of interest for younger demographics where they don’t have the AUM to generate substantial fees, but it’s also important to engage them earlier,” he said. “We do see the replication of some white-glove services that family offices and private wealth firms offer using AI, which requires data and an understanding of the customer.”

The new data-based model of advice could also represent a massive leap forward from the current state of KYC. Because today’s onboarding and updating processes rely heavily on questionnaires, Madej says, clients end up self-reporting risk tolerances that might not reflect their actual appetite or financial situation. By getting direct line of sight into a client’s behaviour and financial information, wealth firms can gain a better understanding of their actual savings needs, ESG priorities, and more over time.

“One year you're a single person, then maybe you get married and have kids. Eventually some people become empty nesters and others become widowers … there's all these different aspects of life,” he said. “Of course, it's not going to be one-size-fits-all. And the data and AI is really going to help people understand that.”