AI-Driven Innovations in Fintech: Applications, Challenges, and Future Trends

Integrating Artificial Intelligence (AI) and Machine Learning (ML) in fintech has revolutionized trading, risk management, fraud detection, and regulatory compliance. AI-driven automation enhances efficiency, while predictive analytics improves market forecasting and decision-making. Case studies demonstrate significant transformations in financial institutions, reducing operational costs and increasing accuracy. However, challenges such as data security, model interpretability, and bias remain critical concerns. This paper explores the impact of AI and ML in fintech, analyzing their benefits, limitations, and future implications for practitioners and regulators. Recommendations for improving AI transparency and regulatory adaptability are also discussed.

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Publication Details

Journal
International Journal of Electrical and Computer Engineering Research
Published
2025-03-15
DOI
https://doi.org/10.53375/ijecer.2025.437
Citations
12
Primary Topic
FinTech, Crowdfunding, Digital Finance
Type
article
Field-Weighted Citation Impact
27.41
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article

AI-Driven Innovations in Fintech: Applications, Challenges, and Future Trends

Asifiqbal Saiyed
12 citations
International Journal of Electrical and Computer Engineering Research
FinTech, Crowdfunding, Digital Finance
27.41
article

AI-Driven Innovations in Fintech: Applications, Challenges, and Future Trends

Asifiqbal Saiyed
article en
12 citations

Abstract

Integrating Artificial Intelligence (AI) and Machine Learning (ML) in fintech has revolutionized trading, risk management, fraud detection, and regulatory compliance. AI-driven automation enhances efficiency, while predictive analytics improves market forecasting and decision-making. Case studies demonstrate significant transformations in financial institutions, reducing operational costs and increasing accuracy. However, challenges such as data security, model interpretability, and bias remain critical concerns. This paper explores the impact of AI and ML in fintech, analyzing their benefits, limitations, and future implications for practitioners and regulators. Recommendations for improving AI transparency and regulatory adaptability are also discussed.

International Journal of Electrical and Computer Engineering ResearchVol. 5(1)
Minot State University (US)
Openalex Percentile: Top 0%
FinTech, Crowdfunding, Digital Finance
27.41
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