A new era: managing green investments through Robo-Advisors

Purpose This study offers evidence about artificial intelligence (AI)’s role in empowering financial advisory services through investigation of Robo-Advisors (RAs) for automatizing investment decisions. RAs use objective algorithms throughout the portfolio selection process, allowing users to diversify their portfolios through the inclusion of Exchange Trading Funds (ETFs) as well as sustainable investments. Design/methodology/approach A multiple case study methodology is used for the investigation of nine RA platforms, namely Vanguard, Betterment, Wealthfront, Axos Invest, E*Trade Core Portfolios, Ellevest, Merrill Guided Investing, Acorns and SoFi Robo Portfolios. The study explores the RA platforms’ model in light of the increased demand for Environmental, Social and Governance (ESG) and Socially Responsible Investments (SRIs). Findings Findings highlight a cross-comparison of nine RA platforms according to 19 variables. These are parent companies, Asset under Management (AUM), Initial Minimum Investment, Available Wallet, Cost and Management Fees, Cost and Fixed Commission, Type of RA (Hybrid or Fully Automated), Accounts supported, the presence of dedicated Consultant/human advisor, Target (retail or professional investors), Bank account/cash management account, Platform strengths, Platform weaknesses, Tax strategy, and finally the presence of ESG and SRI funds under the Sustainable Financial Disclosure Regulation (SFDR)’s articles 6-8-9. Case studies are analysed and compared along with their advantages, similarities and differences. Research limitations/implications By considering existing theoretical models, the study contributes to the AI’s theoretical progress, specifically in the domain of RAs’ impact on the conventional sustainable financial system. Originality/value The research highlights the importance of RAs in democratising access to investments, helping investors in market timing, and clarifying the role of AI for sustainable investments.