Author(s): J�rg Orgeldinger
After the two revolutions in finance over the last century – the efficient market mathematical finance revolution in the 1950s and the behavioral finance revolution in the 1970s now the third finance revolution with "machine finance" began. Robo-advising combines AI and financial expertise to offer accessible and personalized financial guidance. It analyzes data, optimizes portfolios, and provides lower-cost investment strategies. Robo-advisors automate tasks like portfolio rebalancing and offer efficiency and rational decision-making. However, concerns regarding data privacy, algorithmic bias, and regulations need attention. This article explores the benefits, challenges, and regulatory landscape of robo-advising. It emphasizes the support robo-advisory services provide in minimizing risk, generating returns, and maintaining portfolios. They offer an efficient alternative to traditional advisors, using technology and expertise for personalized investment guidance. Further on the fee structure of robo-advisors and the benefits they offer to financial advisors are described. It explains that traditional financial advisors typically charge fees ranging from 1% to 1.5% of total assets managed, while robo-advisors charge between 0% and 0.25% for basic services. The abstract also explores the impact of fees on investment performance and introduces the concept of robo-advisors using index ETFs to minimize fees. It further explains the two main types of robo-advisors: hybrid robo-advisors and pure robo-advisors. Additionally, the article provides examples of prominent robo-advisor providers and their assets under management. It concludes by highlighting the potential influence of artificial intelligence on robo-advising, including data analysis, personalized recommendations, and improved communication with investors.