In the dynamic landscape of asset management, where client demands are in a constant state of flux, the role of asset managers is evolving at a rapid pace. This is particularly evident in the case of Edwin Leong, Head of Product Innovation and Research at RHB Asset Management, who shared his insights at the Malaysia Wealth Management Forum 2026. His perspective offers a fascinating glimpse into the future of product innovation and the integration of emerging technologies like artificial intelligence (AI) in asset management.
The Shifting Market Dynamics
Leong's insights highlight a critical shift in client preferences. Firstly, income-oriented strategies are currently dominating the market, with a strong demand for products that utilize call option premium strategies to deliver structured and repeatable income. This trend reflects a broader shift in client expectations towards predictability and transparency in income generation. Secondly, there is a resurgence in equity exposure, with clients allocating capital to technology, gold equity, and broad Asia ex-Japan strategies as confidence in listed markets recovers.
Malaysia's Fixed Income Landscape
One of the key insights from Leong's presentation is the structural constraint of Malaysia's fixed income market. The market is heavily skewed towards local strategies, dominated by institutional and government-linked capital. This creates a challenge for offshore fixed income strategies, as currency hedging costs remain a binding constraint on their viability for Malaysian investors. The returns must clear a meaningful hurdle before they make commercial sense, and the net returns must deliver something above the local fixed income market.
AI as a Tool for Asset Allocation
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 sits at the pragmatic end of the AI spectrum, where the firm has ringfenced a specific function, tactical asset allocation, and applied an AI model to that task alone. The fundamental research capability remains human-led, and the AI overlay operates as a complement rather than a substitute.
The Evolving Relationship Between Asset Managers and Distribution Partners
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.
Conclusion
Leong's pragmatic approach suggests a firm innovating with discipline, guided by what the market is actually asking for rather than by what the industry finds fashionable to talk about. As the asset management industry continues to evolve, the integration of emerging technologies like AI will play a pivotal role in shaping the future of product innovation and the delivery of value to clients. In my opinion, the ability to adapt to changing market dynamics and client preferences will be a key differentiator for asset managers in the years to come.
