Artificial Intelligence–Driven Fraud Detection in FinTech: Strengthening Cybersecurity Against Digital Financial Scams

Authors

  • Sana Ullah Khan MS Artificial Intelligence, The Islmia University of Bahawalpur, Pakistan
  • Umair Zafar Student, Indiana State University, USA
  • Shamikh Imran Department of Computer Science, Abbottabad University of Science and Technology, Havelian, KPK, Pakistan
  • Muhammad Ali Master's Student, Graduate School of Design, Harvard University, USA

DOI:

https://doi.org/10.63544/jbii.v5i6.116

Keywords:

Anomaly Detection, Artificial Intelligence, Cybersecurity, Digital Financial Scams, FinTech, Machine Learning

Abstract

Artificial intelligence (AI) has transformed fraud detection, enabling financial institutions to spot suspicious transactions, predict new fraud trends, and boost cybersecurity to combat digital financial crimes. The research included applying AI for fraud detection and cybersecurity enhancement in the FinTech sector. The study used a quantitative research design, and primary data were gathered from 385 respondents from diverse organizations like FinTech, digital banks, payment service providers and cybersecurity firms in Pakistan through a structured questionnaire. The data were analysed using SmartPLS 4. Descriptive statistics summarized respondents' perceptions of artificial intelligence, machine learning capabilities, real-time transaction monitoring, anomaly detection, and effectiveness of cybersecurity. Results indicated a high inter-item consistency for all study constructs. The mean values of AI-based fraud detection, machine learning capability, actual-time transaction monitoring and anomaly detection were in the range of 4.02 to 4.18, 4.09 to 4.27, 4.22 to 4.35 and 4.18 to 4.32 respectively. The findings revealed that the respondents recognized AI as a valuable tool for improving the accuracy of fraud detection, automating manual inquiries, detecting unusual transaction patterns, and strengthening the security of digital financial systems. The average results were high, demonstrating high confidence in the intelligent fraud detection technologies in preventing financial fraud and improving the organization’s security performance. The study found that AI and machine learning, combined with real-time monitoring and anomaly detection, offered robust protection against digital financial fraud and improved the security, adaptability, and resilience of FinTech. The results offered practical insights for financial institutions, cybersecurity specialists, technology developers, and policymakers focused on enhancing digital financial security through intelligent fraud-detection frameworks.

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Author Biographies

Sana Ullah Khan, MS Artificial Intelligence, The Islmia University of Bahawalpur, Pakistan

Umair Zafar, Student, Indiana State University, USA

Shamikh Imran, Department of Computer Science, Abbottabad University of Science and Technology, Havelian, KPK, Pakistan

Muhammad Ali, Master's Student, Graduate School of Design, Harvard University, USA

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Published

2026-06-20

How to Cite

Khan, S. U., Zafar, U., Imran, S., & Ali, M. (2026). Artificial Intelligence–Driven Fraud Detection in FinTech: Strengthening Cybersecurity Against Digital Financial Scams. Journal of Business Insight and Innovation, 5(6), 72–82. https://doi.org/10.63544/jbii.v5i6.116

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