Artificial Intelligence and Machine Learning in Financial Technology: Opportunities, Risks, and Regulatory Challenges

Abstract

Artificial Intelligence (AI) and Machine Learning (ML) have rapidly developed into technologies in the Financial Technology (FinTech) industry, making things run smoother such as fraud detection, customer experience, and financial inclusion. However, their rapid adoption has also introduced challenges relating to cybersecurity, algorithmic bias, data privacy, and regulatory compliance. We checked out what is possible with AI and ML, what could go wrong and rules we have to follow in Nigeria's FinTech sector. A descriptive survey research design was adopted, getting people from FinTech firms, banks, government regulators, and AI experts involved, from a population of we had 2,500 people total, and from that we chose 345 people to respond using the Yamane formula, while data were collected through structured questionnaires and analyzed using descriptive and inferential statistics in SPSS Version 29. What we found is AI and ML help banks work faster, stop fraud more, spend less money to run things and keep customers satisfied. The study also established that successful regulatory frameworks help make sure AI is used safely and ethically even though security and privacy are still big concerns. The study shows that AI and smart tech are key to modernizing finance and growing the economy for the long run. It says it need stronger AI governance, enhanced cybersecurity measures, regular algorithm audits, and stricter compliance with data protection regulations to keep AI safe and fair.