Page 107 - Azerbaijan State University of Economics

THE JOURNAL OF ECONOMIC SCIENCES: THEORY AND PRACTICE, V.83, # 1, 2026, pp. 107-131

From Mobile Trading to Intelligent Investing: A Bibliometric and
Thematic Review of AI-Driven Financial Investments

Amit Mishra 1 (Corresponding) , Vibhuti Tripathi 1
1 School of Management Studies, Motilal Nehru National Institute of Technology,

Allahabad, Prayagraj, Uttar Pradesh-211004, India
2 Department of Management, Indira Gandhi Delhi Technical University for
Women, Kashmere Gate, New Delhi-110006, India
ORCID ID: 0009-0005-8340-1460, [email protected]
ORCID ID: 0000-0001-9550-580x, [email protected]

https://doi.org/10.30546/jestp.2026.85.01.0131

Received: November 26, 2025; accepted April 24; published online June 05, 2026

ABSTRACT
Mobile stock trading apps with artificial intelligence (AI) capabilities are
revolutionising retail investing and financial decision-making globally. These
platforms have attracted a lot of interest from retail investors due to their rapid
digitalization and AI-based investment capabilities, but the research that has been
done so far is still dispersed across disciplines and geographical areas. To bridge this
gap, the current study conducts a bibliometric and thematic analysis of research on
mobile stock trading applications and AI-based investment decision-making. The
research integrates the PRISMA framework with Khanra and Dhir's methodology.
For the final synthesis, 243 Scopus-indexed articles that met the preset inclusion and
exclusion criteria were included. The findings reveal that although the earliest
publication related to retail investment appeared in 1983, literature specifically
focused on mobile stock trading applications emerged after 2013, with a rapid rise in
publications since 2021. China, the United States, and Turkey were the prominent
contributors, with Finance Research Letters being the top leading journal. Based on
the author co-authorship network analysis, a total of 18 authors are interconnected
with each other, comprising four clusters with an inclusion threshold of 5 citations.
The thematic analysis identified four major clusters: AI-driven investment and
sustainability, behavioural biases in AI-assisted investing, fintech platform adoption,
and retail investor decision-making through mobile trading applications. However,
stronger regulatory frameworks, increased investor awareness, better AI literacy,
ethical governance systems, and more thorough empirical research on post-adoption
investment behaviour and long-term investor results are necessary for this sector to
flourish sustainably.

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