In the dynamic landscape of wealth management, where investment choices proliferate and client expectations evolve, Morningstar's Nicolas Gisbert offers a compelling perspective on smarter fund selection. His insights, shared at the Hubbis Malaysia Wealth Management Forum 2026, underscore the importance of a disciplined, transparent, and fundamentally driven approach to navigating the complexities of the investment universe. Gisbert's presentation, titled 'Smarter Fund Selection and Monitoring in a Changing Investment Landscape', is a call to action for wealth managers to reevaluate their strategies in light of the expanding investment options and shifting client preferences.
Expanding Horizons: The Evolving Investment Landscape
Gisbert begins by highlighting the three forces reshaping the fund selection landscape. Firstly, the investment choice has expanded significantly, moving beyond mutual funds to include ETFs, private assets, and alternatives. This diversification, while offering more opportunities, also introduces complexity. Secondly, the data and technology revolution, particularly the integration of AI, is transforming how data is collected, analyzed, and consumed. For Morningstar, this presents both internal productivity gains and external client-facing opportunities, especially when anchored to verified research and structured data.
Thirdly, personalisation is becoming a structural trend. Client preferences, such as ESG considerations, Shariah compliance, and industry exclusions, are increasingly important. AI is expected to play a pivotal role in making customized portfolios more scalable and accessible. Gisbert emphasizes that personalisation is not solely about ESG but about recognizing the diverse objectives, constraints, and preferences of investors, and then building portfolios that reflect these nuances.
Morningstar's Expanding Research Universe
Morningstar's data, Gisbert notes, has become part of the global language of investing. The firm covers a broad spectrum of investment types and market participants, including managed investments, public and private companies, ESG-rated securities, DBRS credit-rated securities, ETFs, model portfolios, private market data, and retirement solutions. This breadth is crucial because fund selection is no longer confined to a narrow mutual fund universe. Wealth managers and advisers must assess products across public and private markets, active and passive strategies, liquid and semi-liquid vehicles, and conventional and sustainability-oriented mandates.
Morningstar's capabilities span research and ratings, data and analytics, indexes, managed portfolios, credit ratings, private market insights, and ESG research. Gisbert argues that this broader ecosystem reflects the interconnected nature of investment selection, where fund research, portfolio construction, index design, asset allocation, and client advice all depend on consistent data and comparable analysis.
A Five-Step Fund Selection Process
Gisbert outlines Morningstar's fund selection framework, which he summarizes in five steps. The first step is identification, where wealth managers define the relevant universe by asset class, sector, region, domicile, category, and other criteria. This foundational step ensures that a fund can be properly judged against an appropriate peer group and investment objective.
The second step is quantitative screening, which typically involves building a long list and applying scorecards based on measurable criteria. While performance is part of this process, Gisbert cautions against relying too heavily on it. Alternative assessment methods, such as multi-factor analysis, attribution, risk-adjusted return metrics, active share, alpha consistency, peer group comparisons, qualitative factors, and fees, provide a more comprehensive view of a fund's quality and future potential.
The third step is qualitative screening, where Morningstar's analyst-led research becomes central. Analysts assess whether the fund has the people, process, and parent structure required to support future performance. The fourth step is product and operational due diligence, which includes understanding the manager, investment process, operational infrastructure, risk controls, and wider interaction points around the fund.
The fifth step is portfolio integration and monitoring. A fund should not be assessed in isolation; wealth managers must understand how it fits within a client portfolio, how it affects diversification, and whether it aligns with the client's risk profile. Monitoring should continue after allocation, with regular performance reviews, risk metric tracking, material change assessment, and long-term consistency evaluation. Manager changes are particularly important, as they can affect the original basis for selection.
Looking Beyond Past Performance
Gisbert emphasizes that past performance should not be the dominant basis for fund selection. Instead, selectors should look at risk-adjusted returns, consistency of alpha generation, peer comparisons, fees, active share, and qualitative factors. Active share can be particularly useful in determining whether an active manager is genuinely taking differentiated positions or closely tracking a benchmark while charging active fees. Fees are also highlighted as a key determinant of outcomes, with fee pressure intensifying across asset management.
For end investors, costs matter because they directly reduce net returns. A strong gross return can be significantly weakened by excessive fees, poor structure, or inefficient implementation. Gisbert stresses that fund selection should combine quantitative evidence with qualitative judgment, as numbers can identify candidates but do not always explain whether a manager has a repeatable edge.
The Morningstar Medalist Rating Framework
Gisbert explains Morningstar's Medalist Rating, the qualitative assessment used to evaluate funds on a forward-looking basis. The framework is built around three pillars: People, Process, and Parent. The People pillar assesses the quality, experience, depth, continuity, and alignment of the investment team, including the tenure of portfolio managers and the stability of the team. The Process pillar evaluates security selection, idea generation, valuation discipline, portfolio construction, risk management, and capacity, aiming to understand whether the manager has a repeatable investment process and the resources to execute it consistently.
The Parent pillar looks at the asset management firm itself, including ownership, financial strength, organizational stability, culture, stewardship, and regulatory or compliance standards. Together, these pillars support Morningstar's ratings: Gold, Silver, Bronze, Neutral, and Negative. A medal rating indicates Morningstar's view that a strategy has positive alpha potential, while Neutral or Negative ratings indicate lower conviction.
Due Diligence and Portfolio Fit
Gisbert emphasizes that fund selection should not stop once a shortlist has been created. Due diligence remains essential, as wealth managers must understand the manager's interaction points, from the chief investment officer and research analysts to risk, dealing, sales, clients, and external fund relationships. This helps assess whether the fund is supported by a coherent operating model and whether there are risks that may not show up in a performance screen.
Portfolio fit is equally important. A selected fund must make sense within the client's wider asset allocation. Gisbert highlights risk budgeting, portfolio look-through analysis, and correlation assessment as key tools. Portfolio X-ray analysis can help advisers understand the underlying holdings and exposures inside a fund, while correlation analysis can show whether the fund genuinely improves diversification or simply adds similar risks in another form.
Common Pitfalls in Fund Selection
Gisbert identifies several recurring mistakes in fund selection. The first is chasing performance, where investors often gravitate towards funds with strong recent returns, which may not persist and may reflect market conditions rather than manager skill. The second is ignoring fees, as even a well-managed fund can deliver weaker client outcomes if fee levels are not competitive or clearly justified. Poor diversification, neglecting risk assessment, and overlooking fund manager changes are also common pitfalls.
AI, Data, and the Future of Research Consumption
Gisbert concludes by discussing Morningstar's position in the AI revolution. He argues that Morningstar's advantage lies in the combination of trusted data, accumulated research, and analyst-reviewed content built over more than 40 years. AI becomes more useful when grounded in high-quality source material rather than open-ended information retrieval. Morningstar has developed an MCP server, connecting its universe, database, and research with AI tools like Claude, Copilot, and ChatGPT, allowing users to ask questions within its research environment and receive answers grounded in verified data.
This shift is already changing client conversations, as clients can query data and insights directly through AI-enabled workflows. Gisbert emphasizes that AI is only as good as the data and research behind it, and the opportunity lies in making trusted research easier to access, not replacing the discipline that produced it. This has implications for fund selection, as AI can help collect, process, and surface information more efficiently, but the research framework still matters. Without strong data, consistent methodology, and human oversight, AI can amplify weak inputs rather than improve decision-making.
A More Disciplined Standard for Fund Selection
In conclusion, Gisbert argues that fund selection is becoming more demanding. The investment universe is broader, client preferences are more specific, and technology is changing how research is delivered. However, the basic requirements remain unchanged: selectors must understand the market, know the client, and know the product. For wealth managers in Malaysia, the message is practical. A smarter fund selection process should begin with a defined universe, apply meaningful quantitative filters, incorporate qualitative research, complete proper due diligence, and assess how each fund fits within the client's broader portfolio.
It should also remain active after selection, with monitoring of performance, risk, costs, portfolio role, and manager changes essential to ensuring that a fund continues to serve the client's objectives. Gisbert's message is that better fund selection is not about finding a single perfect metric but about combining transparency, independent research, long-term thinking, data quality, and disciplined monitoring into one coherent process. 'Good fund selection is fundamentally about improving investor outcomes,' he says, 'and that requires more than looking at what performed well last year. It requires understanding what is inside the fund, why it belongs in the portfolio, and whether it continues to do the job.'
