Robo-Advisors: Automated Algorithm-Driven Wealth Management Services - A Literature Review

Abstract

Purpose: Robo-advisors have transformed personal finance management by offering automated, algorithm-driven financial advice to retail investors. Advances in technology and AI have made these services increasingly popular. This study reviews the literature on the adoption and impact of robo-advisory services, exploring how they influence investor behavior.

Design/Methodology/Approach: This study analyzes the adoption of robo-advisors from 2008 to 2024 by examining secondary data gathered mainly from Google Scholar, along with a selection of papers from Scopus. The focus is on uncovering the key factors that influence investor preferences and evaluating the effectiveness of these automated investment platforms.

Findings: Several factors influence robo-advisory performance, including asset allocation, portfolio management, and rebalancing strategies. Adoption is driven by demographics such as millennials, financial literacy, and trust in technology. Investors with lower risk tolerance and shorter investment horizons, particularly women and older individuals, favor sustainable investments. While AI enhances service personalization, regulatory frameworks remain inadequate, especially regarding risk management. In India, robo-advisors attract younger, male investors, with increased platform use during market volatility. Sustainable and ethical investing is gaining popularity among younger, cost-conscious users. Future research should address regulatory issues, explainable AI (XAI), and anti-money laundering measures in robo-advisory services.

Originality: This study contributes to the literature on robo-advisory by analyzing adoption factors, performance metrics, and investor preferences. It highlights key gaps in current research, especially in regulatory and technological areas, offering a roadmap for future studies.

Paper Type: Review of Literature