In the dynamic landscape of asset management, where client demands are in a constant state of flux, the traditional roles of asset managers are evolving. The focus is no longer solely on manufacturing funds and waiting for distribution; instead, it's about actively reading market trends, identifying gaps in advisory portfolios, and leveraging emerging technologies like artificial intelligence (AI) to enhance investment decision-making. This shift is particularly evident in the insights shared by Edwin Leong, Head of Product Innovation and Research at RHB Asset Management, during the Malaysia Wealth Management Forum 2026. His perspective offers a unique glimpse into the evolving strategies of asset managers and the challenges they face in a rapidly changing market.
Following the Flows
One of the most striking trends in client capital movements, as highlighted by Leong, is the dominance of income-oriented strategies. Specifically, products that utilize call option premium strategies to deliver structured and repeatable income are in high demand. This shift reflects a broader change in client expectations, with investors seeking predictability and transparency in how their income is generated. Beyond income, there's also a noticeable return of flows into products with full equity exposure, particularly in technology, gold equity, and broad Asia ex-Japan strategies. This trend indicates a recovery in confidence in listed markets, with clients seeking a balance between stable cash generation and participation in equity upside.
The Fixed Income Constraint
Leong's insights also shed light on the challenges within Malaysia's fixed income market. The market remains heavily skewed towards local strategies, dominated by institutional and government-linked capital. This structural limitation presents both an opportunity and a constraint. While it may limit the availability of safer, internationally focused options, it also opens the door for differentiated strategies that can deliver above-market returns through retail and bank distribution channels. However, the critical constraint remains the hedging cost. Any offshore fixed income strategy must clear the hurdle of currency hedging and associated fees before it can be considered viable for Malaysian 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 process. This approach is pragmatic, focusing on a specific decision point where emotional bias is a known risk, rather than attempting to replace the entire investment process with machine learning. By ring-fencing tactical asset allocation and using AI as a complement to human-led fundamental research, RHB is setting a useful example for the Malaysian market, where many asset managers 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.
Conclusion
In conclusion, the insights shared by Edwin Leong at the Malaysia Wealth Management Forum 2026 offer a compelling glimpse into the evolving strategies of asset managers. From the dominance of income-oriented strategies to the challenges and opportunities within Malaysia's fixed income market, and the pragmatic adoption of AI for asset allocation, the asset management landscape is undergoing significant transformation. For RHB Asset Management, the path forward involves maintaining its fundamental research heritage while selectively adopting new tools that respond to demonstrable client demand. This approach, guided by market needs rather than industry trends, suggests a firm innovating with discipline and a deep understanding of its clients' evolving expectations.
