A study of almost 1000 research papers in the field of digital finance has mapped out how technology, investor behaviour, and financial-market risk are connected. The work identified three distinct foundations rather than a single framework with implications for understanding how psychological factors influence financial decisions as well as how to develop viable algorithms that provide automated investment guidance.
The team used standard bibliometric analysis to find patterns and relationships across the literature published in this niche from 1991 to 2025. They carried out co-citation analysis to identify research that is frequently cited together, as well as keyword analysis to trace connections between research areas. Details are reported in the International Journal of Business and Emerging Markets.
Four main research streams were found: FinTech (financial technology) and investor behaviour, artificial-intelligence-driven investment decisions, market prediction, and automated trading and risk management. FinTech, market volatility and machine learning were identified as established “motor themes”, meaning areas that are both prominent and strongly connected to other research.
The researchers argue that their mapping of the literature has practical implications for developers, financial institutions, and regulators. Automated investment services may require clearer risk information and greater transparency about how recommendations are produced. Regulators could also pay closer attention to model risk and common signals used in automated trading.
Van Nguyen, N., Phan, H.T. and Tran, L.T. (2026) ‘The evolution of the digital finance literature on financial behaviour and market risk’, Int. J. Business and Emerging Markets, Vol. 18, No. 10, pp.1–32.
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