Data Management, Analytics, AI and ML: Helping Elevate the Wealth Management Proposition

The Hubbis Digital Dialogue discussion on July 20 brought together a panel of experts in private wealth management and technology solutions for the industry. Their mission was to debate to what extent data is the new oil for the wealth industry and whether AI and ML are capable of optimising and refining that data as a catalyst for the delivery of a more personalised offering and to help the private banks and other wealth managers achieve better outcomes and also scale their platforms. Andrew Bresler, Deputy General Manager, InvestCloud (APAC), for InvestCloud, also a sponsor of the discussion, was one of the handful of specialists. He offered his perspectives on how technology solutions - if conceived with the right strategies and delivered efficiently and effectively - can facilitate and even fast-track the ability of private banks and other wealth firms to seize the many opportunities on offer in the dynamic Asia Pacific markets. He believes AI- and ML- enhanced data is central to the future of the industry but warns that the pace of adoption will also be reined in by the compliance and governance difficulties in assessing and then controlling the solutions.

InvestCloud is a powerhouse global Software-as-a-Service (SaaS) wealth solutions platform that is one of the fastest-growing B2B WealthTech businesses globally. The firm has the vision to facilitate the digitisation of offerings as financial institutions adjust their business models to rapidly evolving markets, where clients expect a more relevant, personal and real-time proposition – and all for lower fees.

With a strong APAC presence, including offices in Singapore, Hong Kong, Japan and Australia, InvestCloud has been rapidly building partnerships with leading private banks, wealth managers and other players in the investment space to digitise their wealth management operations and enhance client experiences. In past interviews, we have learned how InvestCloud’s modular approach allows clients to upgrade their capabilities, make the most of existing technology investments and promote client growth, client retention and operational efficiencies in a cost-effective and agile manner, rather than a ‘rip and replace’ approach laden with risk.

Global coverage

InvestCloud is today a fully global WealthTech platform provider, offering very simply a single digital cloud native application to help clients retain their private clients and win new clients while driving huge gains in operational efficiency.

The firm provides these solutions for over 700 clients around the world – including private banks, consumer banks and insurance company advisor networks – as well as over 150 asset managers globally. They have just over 6 USD trillion of assets on the platform, supporting over 7,000 user experiences in over 40 countries for over 20 million global investor accounts today. In Asia, they operate through four key office centres, and serve many of the large and leading players in each of those markets, both locally and regionally.

Bresler first observed that the inefficiencies that exist within the wealth industry today are where AI can begin its improvements. He cited a McKinsey report that said data-driven advisors are set to deliver 15 times the value to clients than those that are not data-driven. It was also cited that 91% of all data is incomplete, outdated or inaccurate. “That is the starting point,” he said.

Know your markets

He pointed to the key HNW segment of wealth in Asia that they target for clients with USD2 million to USD10 million of AUM, in other words, just below pure private banking thresholds today, and above the wealth of the rapidly expanding mass affluent market.

“In this key segment, there is both a labour and skillset shortage in the region, with a dearth of experienced relationship managers,” he explained. “They also tend to serve somewhere between 100-200 clients, but only concentrate on 15% to 20% of that book. In this area, leveraging AI and tools that provide recommendations on which activity to prioritize is critical to the success and to gathering more share of wallet.”

He observed that the UHNW segment is more ‘white glove’ and with far fewer clients allocated to each of the very experienced RMs, but even there, they need as much support from data, driving insights and recommendations.

And in the rapid growth mass affluent market across the region, the mission amongst banks and other providers is to improve coverage, achieve scale, reduce cost-to-serve, and of course, garner more clients and share of wallet. “To achieve these goals there has been a widespread drive to deliver a pure digital experience and, at the same time, a desire to make that experience hyper-personal,” Bresler reported. “And data is absolutely central to all that.”

He identified several key trends within wealth management that align with these objectives. One is the wealth continuum, or the need to service clients as they mature and evolve their wealth and their needs, perhaps graduating from retail or mass affluent clients to the HNWI level.

Seeking seamless migration

“The answers are not that simple,” he said, “as the private banking businesses have been very separate from the retail and the mass affluent wealth business. And data is again central to a smooth transition so that any clients are transitioning with the full support of the organisation’s data history and experience, thereby helping deliver a seamless shift.”

The second key theme is content-led wealth management.

“This is all about differentiating client experience through content rather than products or advice, which are oftentimes seen as largely commoditised,” he told guests.

“I think there is a major challenge with content distribution within the industry; imagine for example, a private bank still producing 15 to 20 trade recommendations a day, or more than 3500 of those a year. How do they hit the right client at the right time with the right ideas? Well, again, data and refined data enhanced by AI and ML hold the keys to unlocking that potential.”

Devising a viable data strategy

Bresler then advised banks and other providers to ensure they have an articulated strategy around data in place or in process.

“And oftentimes, the answer is they do not,” he cautioned. “However, we pride ourselves on our InvestCloud digital warehouse, through which we feed data and then translate that into a single language that can be understood by any provider to help build a picture of the client’s DNA. In short, a valid data strategy consolidates and uses data in a way that builds that personalisation and that is fundamental to unlocking the power of AI and machine learning in wealth management.”

Bresler rounded off his observations by pointing to future developments, remarking that the speed and momentum of change have been quite incredible in recent years.

Self-limited acceleration

“However, I do feel things will evolve more slowly in the foreseeable future, due largely to regulation,” he reported. “When I sit with decision makers and recount the advances in AI, ML and in other areas, their excitement rises, but so too do their concerns about governance and compliance around areas that are extremely difficult to comprehend. The worries naturally focus then on the ‘what if we get it wrong’ scenarios. In summary, the use of ML and AI for empowering RMs, yes, that can all advance apace. But direct-to-client solutions without definitive gatekeepers will progress more guardedly.”