Market Insights Financial Wealth Management Digital Investment

Robo-Advisors - Singapore

Singapore

The Robo-Advisors market in Singapore is projected to see assets under management reach US$1,487.00m by 2024.
This is expected to result in an annual growth rate (CAGR 2024-2027) of 10.71%, leading to a projected total of US$2,018.00m by 2027.
Additionally, the number of users in the Robo-Advisors market is forecasted to reach 13.640k users by 2027.
Looking specifically at the average assets under management per user in the Robo-Advisors market, it is expected to amount to US$124.60k in 2024.
In a global comparison, it is worth noting that in the United States currently holds the highest assets under management with US$1,459,000.00m in 2024.
Singapore's robo-advisor market is experiencing rapid growth, driven by the country's technologically advanced financial sector and high demand for automated investment services.

Key regions: Singapore, Asia, Germany, Canada, Europe

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Data coverage:

The data encompasses B2C enterprises. Figures are based on transaction values / revenues / assets under management and user data of relevant services and products offered within the FinTech market.

Modeling approach / Market size:

Market sizes are determined through a combined top-down and bottom-up approach, building on a specific rationale for each market segment. As a basis for evaluating markets, we use annual financial reports of key players, industry reports, third-party reports, publicly available databases, and survey results from primary research (e.g., the Statista Global Consumer Survey). In addition, we use relevant key market indicators and data from country-specific associations, such as GDP, consumer spending, population, internet penetration, smartphone penetration, credit card penetration, and online banking penetration. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited for forecasting digital products and services due to the non-linear growth of technology adoption.

Additional notes:

The market is updated twice a year in case market dynamics change. The impact of the COVID-19 pandemic and the Russia-Ukraine war is considered at a country-specific level.