In the dynamic landscape of asset management, where client demands are in constant flux, the role of asset managers is evolving. No longer confined to traditional manufacturing and distribution, asset managers are now at the forefront of innovation, leveraging emerging technologies like artificial intelligence (AI) to stay ahead of the curve. This transformation is particularly evident in the Malaysia Wealth Management Forum 2026, where industry experts gathered to discuss the latest trends and strategies in product innovation and investment advisory. Among the key insights shared was the evolving relationship between asset managers and their distribution partners, and the innovative use of AI in asset allocation. The panel, chaired by Alex Ng, Managing Director and Head of Intermediary, Asia Client Group at Janus Henderson Investors, featured Edwin Leong, Head of Product Innovation and Research at RHB Asset Management. Leong's insights offered a unique perspective on the shifting market dynamics and the role of AI in asset management.
Following the Flows
Leong's analysis revealed a clear trend in client capital movements. Income-oriented strategies, particularly those utilizing call option premium strategies, are dominating flows. This shift in client expectations towards structured and repeatable income generation reflects a demand for predictability and transparency. Beyond income, there's a resurgence in flows into full equity exposure products, including technology, gold equity, and broad Asia ex-Japan equity. This trend indicates a balanced approach, where clients seek stable cash generation alongside participation in equity upside.
The Fixed Income Constraint
The conversation then turned to Malaysia's fixed income market, which is heavily skewed towards local strategies due to the dominance of institutional and government-linked capital. However, Leong highlighted a growing appetite for differentiated fixed income strategies among retail and bank distribution channels. The critical constraint remains currency hedging costs, which make offshore fixed income strategies less viable for Malaysian investors. Leong emphasized that offshore strategies must offer meaningful returns above local alternatives to gain traction, a challenge that product designers must address.
AI as an Allocation Tool
Leong's most forward-looking contribution was RHB Asset Management's adoption of AI in asset allocation. The firm has launched a strategy that uses an AI overlay to determine monthly asset allocation, removing emotional bias from the process. This pragmatic approach, focused on a specific decision point, offers a useful case study for the Malaysian market, where many asset managers are still in the early stages of AI adoption. By ring-fencing tactical asset allocation and complementing it with human-led fundamental research, RHB is innovating with discipline, guided by client demand.
Bridging Manufacturing and Distribution
Leong's insights underscored the evolving relationship between asset managers and their distribution partners. In a market where actively managed funds are sold rather than bought, asset managers must provide advisory support, market insight, and clear articulation of strategy benefits. The income trend, fixed income constraint, and AI overlay each reflect a different dimension of this challenge. Income strategies demand explainability, fixed income products must overcome hedging costs, and AI tools must build confidence among advisers and clients. RHB Asset Management's pragmatic approach suggests a firm innovating with discipline, guided by market demand rather than industry trends.
