In the dynamic landscape of asset management, where client demands are in a constant state of flux, the role of asset managers is evolving. No longer confined to the traditional confines of fund manufacturing and distribution, asset managers are now at the forefront of navigating shifting market trends and adapting to the needs of their clients. This is particularly evident in the insights shared by Edwin Leong, Head of Product Innovation and Research at RHB Asset Management, at the Malaysia Wealth Management Forum 2026. His perspective offers a fascinating glimpse into the future of asset management, where technology, particularly artificial intelligence (AI), is playing an increasingly pivotal role. But it's not just about the tools; it's about the strategic shift in how asset managers are approaching product innovation and client needs.
The Shifting Market Dynamics
Leong's insights highlight a critical shift in client preferences. Income-oriented strategies are currently dominating the market, with a strong demand for products that use call option premium strategies to deliver structured and repeatable income. This trend reflects a broader shift in client expectations, where predictability and transparency are highly valued. However, this doesn't mean that equity exposure is being overlooked. On the contrary, there's a parallel trend of returning flows into products with full equity exposure, particularly in technology, gold equity, and broad Asia ex-Japan strategies. This dual trend underscores the complexity of client needs and the need for asset managers to offer a balanced approach.
The Fixed Income Constraint
One of the most intriguing aspects of Leong's insights is the discussion on Malaysia's fixed income market. The market is heavily skewed towards local strategies, dominated by institutional and government-linked capital. This structural reason makes it challenging for offshore fixed income products to deliver attractive returns once currency hedging and fees are accounted for. The hedging cost remains a binding constraint, requiring returns to clear a meaningful hurdle before they make commercial sense for Malaysian investors. This constraint has significant implications for product designers, who must consider the net returns and the value proposition for local investors.
AI as an Allocation Tool
Leong's most forward-looking contribution concerned RHB Asset Management's adoption of AI as a tool for asset allocation. The firm has launched a strategy that uses an AI overlay to determine monthly asset allocation, removing emotional bias from the investment process. This approach is particularly interesting because it focuses on a specific decision point where emotional bias is a known risk. By ring-fencing tactical asset allocation and applying an AI model to that task alone, RHB is able to maintain its fundamental research heritage while leveraging the benefits of AI. This pragmatic approach offers a useful case study for other asset managers in the Malaysian market, where many are still in the early stages of AI adoption.
Bridging Manufacturing and Distribution
Leong's contributions across the panel highlighted the evolving relationship between asset managers and their distribution partners. In a market where actively managed funds are sold rather than bought, the asset manager's role extends beyond product construction into advisory support, market insight, and the ability to articulate clearly why a particular strategy makes sense for a specific client segment. The income trend, the fixed income constraint, and the AI overlay each reflect a different dimension of this challenge. Income strategies must be explainable and transparent. Fixed income products must clear a quantifiable hurdle. And AI-driven tools must build confidence rather than creating anxiety among advisers and clients who remain sceptical of algorithmic decision-making.
Conclusion
In conclusion, the insights shared by Edwin Leong at the Malaysia Wealth Management Forum 2026 offer a fascinating glimpse into the future of asset management. The market is shifting, with a strong demand for income-oriented strategies and a return to equity exposure. However, the fixed income constraint and the need for balanced approaches remain significant challenges. AI is emerging as a powerful tool for asset allocation, but its adoption must be pragmatic and focused on specific decision points. Ultimately, the success of asset managers in this evolving landscape will depend on their ability to innovate with discipline, guided by what the market is actually asking for rather than by what the industry finds fashionable to talk about.
