Market Insights Financial Wealth Management Digital Investment

Robo-Advisors - Asia

Asia

By 2024, it is projected that the assets under management in the Robo-Advisors market in Asia will reach a staggering amount of US$103.80bn.
This market is expected to show a strong annual growth rate (CAGR 2024-2027) of 8.89%, resulting in a projected total amount of US$134.00bn by 2027.
Additionally, the number of users in the Robo-Advisors market is expected to reach 6.990m users by 2027.
Furthermore, it is estimated that the average assets under management per user in the Robo-Advisors market in Asia will amount to US$15.73k in 2024.
When comparing this to global figures, it becomes evident that in the United States currently boasts the highest assets under management with a staggering US$1,459,000.00m in 2024.
In China, the demand for robo-advisors is surging as tech-savvy investors seek low-cost, automated investment solutions.

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

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Methodology

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.