THE IMPACT OF ARTIFICIAL INTELLIGENCE ON RISK ASSESSMENT AND FRAUD DETECTION
DOI:
https://doi.org/10.5281/zenodo.17447942Keywords:
Artifcial Intelligence (AI); Risk Assessment; Fraud Detection; Machine Learning; Anomaly Detection; Financial Security; Algorithmic Bias; Data Privacy; Predictive Analytics; Governance.Abstract
The integration of Artifcial Intelligence (AI) in fnancial and organizational systems has transformed traditionalapproaches to risk assessment and fraud detection. Advanced machine learning algorithms, natural language processing,
and anomaly detection models enable organizations to identify complex patterns and irregularities in real time, signifcantly
enhancing the accuracy of risk profling and fraud prevention. AI-driven solutions not only improve efciency by reducing
manual errors but also adapt dynamically to evolving fraudulent schemes, thereby strengthening fnancial security.
However, challenges such as data privacy concerns, algorithmic bias, and the need for transparent governance remain
critical issues for sustainable adoption. This study explores the impact of AI technologies on risk assessment and fraud
detection, highlighting their potential benefts, limitations, and implications for future fnancial and organizational stability.
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