One connected stack for
systematic investment workflows.

MethodTech connects risk modelling, alpha creation, portfolio construction, strategy testing, analytics, and wealth portfolio intelligence into one workflow for modern investment teams.

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Risk Model

Understand Risk

Alpha Machine

Build Signals

Portfolio Construction

Optimise Portfolios

Strategy Builder

Test Strategies

Wealth Management

Serve Clients

Analytics

Explain Outcomes

Products

How MethodTech Fits Into the Investment Process

Risk Model

Alpha Machine

Portfolio Construction

Strategy Builder

Analytics

Wealth Management

Mutual fund intelligence beyond trailing returns.

MethodTech’s Wealth Management platform helps investment teams screen mutual funds, compare managers, build custom fund baskets, and analyse portfolio behaviour using return attribution, risk decomposition, factor exposure, holdings overlap, and basket-level diagnostics.

Most mutual fund analysis still starts with trailing returns, rankings, and category comparisons. That is not enough.

A fund may outperform because the manager picked better stocks, took more market risk, leaned into the right style factor, benefited from sector exposure, or simply rode a favourable regime. MethodTech helps wealth managers understand the difference. 

The platform combines fund screening, manager analysis, factor exposure, return decomposition, risk decomposition, and basket construction into one workflow. Users can move from fund discovery to shortlist creation, from individual fund analysis to basket building, and from basket allocation to portfolio-level diagnostics.

Fund Screening helps teams compare mutual funds using a deeper analytical framework than trailing returns alone. 

Basket Builder helps teams combine funds into weighted portfolios and analyse how those funds interact together. 

Analytics Workspace shows portfolio-level outputs across returns, holdings correlation, risk decomposition, factor exposure, and holdings. 

What It Helps You Do

  • Screen and compare mutual funds across returns, ratios, risk, and exposures 

  • Analyse whether fund performance came from market, style, industry, dividend, or stock-selection effects  

  • Identify manager style drift and changes in portfolio positioning  

  • Evaluate forward-looking risk across market, style, industry, and idiosyncratic components  

  • Build weighted mutual fund baskets and compare them against benchmarks 

  • Analyse holdings overlap, fund correlations, blended factor exposure, and concentration risk