A Robo-Advisors is a type of financial advisor that uses computer algorithms to provide automated investment advice and manage portfolios for clients. These online platforms use complex mathematical models and historical data to analyze market trends and make investment recommendations based on the client's risk tolerance and investment goals. Robo-advisors typically offer a variety of investment options, such as index funds and exchange-traded funds (ETFs). Unlike traditional human financial advisors, robo-advisors operates around the clock, and often have lower fees. The advantage of these services lies in the passive role of the investor, who may not want or cannot afford ongoing personal monitoring of their portfolio development.
Keyplayers in this market are Wealthfront, Schwab Intelligent Portfolios and Betterment.
Automated online portfolio management of private assets
Currently, the robo-advisor market is experiencing significant growth, with an increasing number of consumers turning to automated investment advice platforms. One trend that has emerged in the market is the integration of artificial intelligence and machine learning technologies, which enable robo-advisors to provide more personalized investment recommendations to clients. Another trend is the expansion of robo-advisory services to encompass a broader range of financial services, such as retirement planning, tax optimization, and debt management. Several factors are driving the growth of the robo-advisor market. One key factor is the increasing demand for low-cost investment advice, as traditional financial advisors can be expensive and often require high minimum investment amounts. Another factor is the rise of tech-savvy millennials, who prefer digital platforms for financial services. Additionally, the COVID-19 pandemic has accelerated the shift to online financial services, including robo-advisors, as more consumers have turned to digital channels for their financial needs. The robo-advisor market is expected to continue to grow in the coming years. This growth is expected to be driven by factors such as increasing demand for low-cost investment management solutions, the rising popularity of passive investing, and the continued development of artificial intelligence and machine learning technologies.
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.
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.
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.