Robo-advisers: Democratizing access to financial advice

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Robo-advisers: Democratizing access to financial advice

Robo-advisers: Democratizing access to financial advice

Subheading text
Robo-advisers set to democratize access to financial advice and eliminate human error risks
    • Author:
    • Author name
      Quantumrun Foresight
    • September 13, 2023

    Insight summary



    Robo-advisers are becoming the new financial advisors, offering algorithm-based services to customers online. These platforms are efficient and cost-effective, potentially yielding higher returns. While robo-advisers democratize access to financial advice and eliminate human error risks, they may also lead to job displacement and increasing concerns about algorithmic bias and market crashes. 



    Robo-advisers context



    Artificial intelligence (AI) is changing how market intermediaries and asset managers operate and conduct business. Many companies now utilize AI and machine learning for advisory support, risk management, client identification, monitoring, trading algorithm selection, and portfolio management. Online automated investment platforms, or robo-advisers, are gaining global popularity. 



    According to a 2021 European Parliament study, robo-advisers are predicted to manage approximately USD $2.85 trillion worldwide. Initially adopted by start-ups, major financial institutions like Vanguard, Schwab, and Fidelity have started offering robo-advice services.



    A robo-adviser is a software operated by a regulated financial intermediary, offering algorithm-based services to customers online. This approach can be more efficient and cost-effective for investors, potentially yielding higher returns. Robo-advisory presents unique challenges, including standardized human-machine interaction, investment process opacity, the risk of defective algorithms, and concerns about financial stability. 



    Modern robo-advisers typically offer both investment advice and portfolio management, with human interaction primarily focused on customer support. These advisers mainly invest in exchange-traded funds (ETFs) and employ diversification to mitigate investment risks. Passive robo-advisers minimize portfolio adjustments, while more advanced active strategies use sophisticated algorithms to attempt to outperform the market. These robo-advisers can lower costs by reducing human involvement, allowing more investors to access advisory, investment, and wealth management services that may have been previously unaffordable. Global regulators are examining the advantages and drawbacks of robo-advisers, as well as evaluating if current regulatory frameworks can effectively address the potential risks and challenges of these financial algorithms.



    Disruptive impact



    Robo-advisers construct ideal portfolios tailored to investors' preferences, often using a variation of Modern Portfolio Theory, which emphasizes allocating funds to stocks that don't have a perfect positive correlation. These advisors typically distribute funds between risky and risk-free assets, with the allocation determined by the investors' objectives and risk tolerance. As economic conditions shift, robo-advisers can continually monitor and rebalance the portfolio by adjusting the proportions of risky and risk-free assets.



    Another area that robo-advisers can optimize is tax-loss harvesting, the practice of selling securities at a loss to reduce capital gains tax often carried out near the end of the tax year. By doing so, investors can avoid taxes on that income. To maintain portfolio allocation and capitalize on potential market upswings, investing in comparable security is crucial. Robo-advisers automate this process, enabling users to easily take advantage of tax-loss harvesting.



    However, increasing regulatory concerns and challenges can slow down the growth of the robo-adviser market. A faulty or outdated algorithm may generate results that consistently underperform the desired investment returns. This flawed advice could impact numerous investors simultaneously, possibly directing their funds into unsuitable investments and creating market imbalances. 



    Inexperienced clients could misunderstand the software's questions, provide incorrect data, or misinterpret the given advice. The algorithm's perceived unbiased and objective nature might also lead clients to overly depend on the output. Moreover, the investment process is often opaque. Clients are unaware of the exact workings of the algorithm or other factors influencing the software's decisions. 



    Implications of robo-advisers



    Wider implications of robo-advisers may include: 




    • Robo-advisers democratizing access to financial advice, making it more accessible to individuals who cannot afford traditional financial advisors. This feature could help close the wealth gap and promote financial inclusion.

    • Improved investment performance over the long term, benefiting individual investors, pension funds, and other institutional investors.

    • The elimination of human error risks and bias that can occur with traditional financial advisors, leading to more accurate investment decisions and reduced fraud.

    • People relying on data-driven investment decisions rather than emotional reactions to market volatility, leading to more stable investment behavior and reducing the impact of market swings.

    • Job displacement in the financial services industry, particularly among traditional financial advisors. 

    • Increasing concerns about algorithmic bias or algorithms going rogue, leading to market crashes and unexplainable volatility.

    • Governments limiting the use of robo-advisers until more concrete and standardized regulations can be established to protect investors.



    Questions to consider




    • If you’re an investor, would you consider using robo-advisers? Why?

    • What are the other potential challenges of relying on robo-advisers for investment strategies and decisions?


    Insight references

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