Artificial Intelligence in Financial Decision-Making: An Integrative Review of Applications, Governance Challenges and Future Research
DOI:
https://doi.org/10.68050/JAMS.2026.519Keywords:
Artificial intelligence; financial decision-making; predictive analytics; financial risk management; AI governance; explainable AIAbstract
Artificial intelligence is increasingly shaping financial decision-making, particularly in predictive analytics, risk assessment, fraud detection and portfolio management. However, research on these applications remains fragmented and often gives limited attention to the governance arrangements needed for their responsible and reliable use. This study presents an integrative review of the applications, benefits and governance challenges of AI in financial decision-making. English-language scholarly publications issued between January 2018 and June 2026 were identified through Google Scholar and backward reference searching. Following title, abstract and full-text screening, 59 publications were selected and analysed using thematic synthesis. The findings show that AI can improve analytical efficiency, forecasting, risk monitoring, fraud detection and investment analysis. Nevertheless, these benefits depend on data quality, model reliability and explainability, cybersecurity, appropriate human oversight and clear regulatory accountability. The review also identifies important research gaps relating to algorithmic bias, systemic financial risk, cross-border data governance, human-AI collaboration and workforce adaptation. By examining technological applications alongside their organisational, ethical and regulatory conditions, this review offers an integrated understanding of how and under what conditions AI can support reliable financial decision-making. It concludes that AI should complement rather than replace professional judgement, particularly in high-stakes financial settings.
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