Robo-Advisors as a FinTech Disruption: A Bibliometric Analysis

Abstract

Purpose: The study aims to provide a comprehensive bibliometric analysis of robo-advisory research to map its intellectual structure, thematic evolution, and emerging trends within the FinTech ecosystem.

Design/Methodology/Approach A dataset of 459 Scopus-indexed publications from 2014 to 2025 was analysed using Biblioshiny (R) and VOSviewer. The analysis covered performance analysis, co-occurrence networks, thematic mapping, and citation analysis to identify influential authors, sources, and research clusters.

Findings: The results reveal a sharp increase in publications after 2018, reflecting rising academic and growing interest in AI-driven financial services. India, the United States, and China lead in research output, while the United States exhibits the highest citation impact. Thematic mapping highlights two dominant research streams: (1) technology-focused themes such as AI, machine learning, and blockchain, and (2) user-centric themes like trust, financial literacy, and adoption behaviour. Emerging topics include algorithmic transparency, explainability, and personalised advisory solutions.

Originality/value: This study consolidates a fragmented body of literature into an organised knowledge structure, providing actionable insights for academics, practitioners, and policymakers. It identifies thematic gaps and future research opportunities in behavioural aspects, regulatory frameworks, and ethical considerations in robo-advisory services.

Paper Type: Review of Literature