Digital and AI-enabled wealth management: The big potential in Asia

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The affluent and mass-affluent segments in Asia, particularly in developing economies, are at a tipping point, creating a new market opportunity for banks and wealth managers in the region. The wealth pool of this group—defined as households with investable assets of $100,000 to $1 million—is projected to hit $4.7 trillion by 2026, up from $2.7 trillion in 2021, as Asians’ incomes rise, according to McKinsey analysis. For banks and wealth managers, the potential incremental revenue from serving these clients will be $20 billion to $25 billion—contributing more than half of the industry’s revenue growth in Asia over the next three years (Exhibit 1).

This is a rare opportunity in financial services—a fast-growing segment that is currently underserved and, according to our recent research, increasingly open to paying for wealth management services. The challenge for banks and wealth managers is to tailor their approach across four dimensions: segmented customer value propositions, reimagined digital engagement, AI-powered decision making and core technology, and the right operating model and talent.

Market changes create an opportunity

The market potential in the affluent and mass-affluent segments is not new. Leading wealth managers and banks have long recognized the opportunity, but several challenges prevented them from winning over these investors. One is the traditional high-cost servicing model, which is based on in-person meetings with relationship managers. In addition, many affluent and mass-affluent investors have been reluctant to pay advisory fees. They have generally preferred basic asset classes (such as cash and real estate) and have not seen the value in professional wealth management.

These challenges have started to ease in the past several years as technology has reduced costs for wealth advisors and increased access for their clients. In McKinsey’s latest Personal Financial Services Survey,1 approximately 80 percent of affluent and mass-affluent respondents in Asia say they would or might consider receiving advisory services remotely through digital channels (Exhibit 2). Moreover, 87 percent of investors in developed markets within Asia and 64 percent in developing markets say they are willing or may be willing to pay advisory fees.2

In summary, the wealth of affluent and mass-affluent customer segments in Asia is growing rapidly. At the same time, these customers have shown an increasing need for advisory services, coupled with a willingness to pay. With the cost to provide those services declining, the economics suggest that this pair of segments is a compelling opportunity for banks and wealth managers in the region.

Rethinking wealth management

To capture this opportunity, banks and wealth managers can use digital products and services that are more personalized and tailored to the needs of specific customer segments, and which have a lower cost to serve than traditional client interactions. To achieve these advantages, banks and wealth managers will need a full-stack approach across four dimensions: segmented customer value propositions, reimagined digital engagement, AI-powered decision making and core technology, and the right operating model and talent (Exhibit 3).

More granular customer segmentation and value proposition

Clients need to be at the heart of the offering, with banks and wealth managers making personalized recommendations based on the needs of specific segments. Even within a seemingly homogeneous group (such as affluent and mass-affluent investors), a great deal of variation exists in investing experience, willingness to make one’s own investment decisions, desire for advice or planning services, attitude toward risk, preference for digital versus face-to-face engagement, and many other variables.

Notably, obtaining the types of insights required to develop a segmented view of the market calls for a new approach—one not based solely on traditional metrics (such as portfolio size and income level) but also incorporating attitudes and behaviors. Such ethnographic or design-thinking methods have become the best practice among leading global wealth managers.

Asian wealth managers can benefit from applying similar methods to identify target segments and to design tailored service offerings, customer journeys, and value propositions that meet the needs of specific customer personas. Exhibit 4 shows examples of two such investor types, along with their value drivers, needs, and preferred journey preferences.

Reimagined engagement with digital tools to improve user experience and internal productivity

Rather than focusing exclusively on in-person client meetings, banks and wealth managers should strike a balance between personal interactions and digital interactions. Innovative user-interface solutions can improve the experience for both customers and relationship managers.

For customers, self-serve digital options should span the entire client journey, from acquisition and onboarding to investment decisions to portfolio management. AI-powered tools delivered via mobile platforms—including 24/7 decision support, financial health checks, budgeting tools, and gamification (for example, reward-based incentives for platform engagement and simulated trading)—can make digital channels far more engaging. Apps can also make analytics-driven investment recommendations, show asset allocations for various portfolios, help clients optimize portfolio risk, offer client-specific portfolio rebalancing, and identify the next best product for clients to consider.

Once clients are enrolled, digital and AI-derived insights can help banks and wealth managers tailor offerings to specific customer needs, as in the following examples:

  • Savings and investment advisory services. Banks and wealth managers can use robotic advisory technology to make specific recommendations about investment strategies, analyze portfolios, change asset allocations, and offer other proactive support based on a customer’s investment goals and risk profile.
  • Insurance advisory services. Companies can provide targeted recommendations about insurance coverage amounts and type (for example, life, general), powered by robotic advisory services based on a client’s stage of life, personal details, level of affluence, spending allocation, tax savings, and other factors.
  • Expense management. Clients can receive a curated analysis of historical spending with recommendations for how to optimize spending, savings, and budget allocation.
  • Tax-loss harvesting. Clients can get access to optimized tax performance on the sale of investments, along with simplified filing of taxes.
  • Debt management. Clients can get recommendations on suggested loan balance transfers, if any, and relevant loan products.

For relationship managers, digital interactions can improve productivity, enable end-to-end client servicing, and enable the bank or wealth manager to aggregate all client data (including internal information and that from third-party sources) into a “single source of truth.” Some banks and wealth managers have developed tools that relationship managers can use during in-person meetings or to support clients remotely (Exhibit 5). Capabilities typically include tracking of KPIs and client management, segmentation, and servicing. Use of such tools contributes to ensuring a consistent experience for clients regardless of whether they engage in person or via digital channels.

AI-powered decision making and advisory, supported by core technology and data

Today, banks and wealth managers can combine data generated inside their organization with data from third-party sources to build a resource for creating more effective client interactions across the full customer life cycle:

  • Customer acquisition. Digital marketing can make customer acquisition more efficient by helping wealth managers understand the needs of people not yet onboarded as clients. Wealth managers can conduct A/B testing on marketing messages and campaigns, develop lead prioritization models, and coordinate with ecosystem partners to build integrated customer acquisition channels.
  • Increasing engagement and wallet share. As soon as prospects become customers, analytics can strengthen the relationship. In the onboarding phase, wealth managers can use an identification engine to determine a financial health score that consolidates information from different sources to a single metric that helps banks and wealth managers determine the optimal level of service and product mix (Exhibit 6). Algorithms can also identify “hidden affluence”—customer assets held with other banks or wealth managers.
  • Client retention. Once the customer is truly engaged, analytics can contribute to customer retention by prompting wealth managers to offer suggestions for maintaining the best portfolio and rebalancing it on a timely basis.

To support this new approach, banks and wealth managers need the right core technology and data layers. Many outsource some services—a practice known as “hollowing out the core.” Another approach to core technology is a cloud-based platform that supports real-time analytics across multiple data sets and service providers while maintaining a single source of truth for all enterprise, transaction, and client data. Underlying components can be connected via a modular structure, reducing operating costs and increasing resiliency.

Operating model and talent for the new approach

For most wealth managers, moving to a digital and AI-enabled wealth management model will require transforming their operating model and building new capabilities. That in turn requires a review of the organizational structure, talent, culture, incentives, and ways of working, with the goal of redesigning these as needed to help the organization’s people deliver value to their customers at scale.

Regarding the operating model, wealth managers need to shift from a push-based sales approach to a needs-based advisory approach. Many wealth managers will need to unlearn established behaviors and ways of working, replacing them with data-driven, personalized recommendations delivered through a hybrid model of remote advisory and personalized service. In this model, an algorithm can look at client-specific factors such as risk tolerance and time horizon to generate a baseline asset allocation across categories. It is critical to couple this with advisors who understand customer needs and further customize the portfolio based on contextual factors. Advisors can also offer support beyond straight portfolio decisions, addressing investment planning, behavioral finance, and even assets with other providers to develop a comprehensive picture of a client’s financial situation.

The operating model cannot deliver results without the necessary human capabilities, so capability building is critical. Most wealth managers provide for product training, but those programs underemphasize human skills, such as behavioral training and relationship building. As technologies like robotic advisory services become table stakes in the industry and players increasingly differentiate themselves based on their overall customer experience, such human skills will become more relevant. They warrant a greater investment of time and organizational focus, along with the usual regulatory and compliance requirements. Most banks and wealth managers will need a dedicated central team to design training modules and source the required faculty.

The current wealth management environment in Asia presents a rare opportunity: a fast-growing market that is hungry for new solutions even as technology is emerging to help banks and wealth managers provide the sought-after offerings. Forward-looking banks and wealth managers that take deliberate steps to rethink every aspect of their business model can put themselves in a position to capitalize.

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