Based on the most commonly-seen models, a typical robo-adviser would ask a client a number of questions to ascertain his/her age, financial goals, risk appetite, investment horizon and financial situation, etc. through an online questionnaire. Next, the robo-adviser would make use of algorithms and data-driven strategy to analyse the collected information and recommend an investment portfolio that suits the risk level and goal of the client.
An algorithm is the process or steps that a computer programme uses to solve a problem. The algorithms of robo-advisers are usually based on a mix of different investment or portfolio theories, models and assumptions.
Many robo-advisers use ETFs which are usually low cost and diversified passive funds as underlying tools to build the client’s portfolio, including different asset class ETFs. But some robo advisers may adopt a different framework and use other asset classes, e.g. non-exchange traded funds as underlying tools. Some robo-advisers may use a buy-and-hold strategy. After building up the portfolio, the robo-adviser may automatically rebalance your pre-defined model portfolio periodically in order to maintain the target asset allocation over time.
Typical robo-advisers usually charge an all-in annual advisory fee as a percentage of the client’s account value. But some may charge other fees such as performance fees, brokerage fees etc. Others may charge fund subscription fees, switching fees and redemption fees if they use non-exchange traded funds as underlying tools.
4 April 2019
