EVALUATING THE EFFECTIVENESS OF AI-BASED FRAUD DETECTION IN DIGITAL BANKING: EVIDENCE FROM UZBEKISTAN (2020–2025)

Urozova Nigora Toshmurodovna,Kuralbayeva Nursulu Kuatbekovna, Oralboyeva Ruxshona Vafoyevna

Authors

Urozova Nigora Toshmurodovna,Kuralbayeva Nursulu Kuatbekovna, Oralboyeva Ruxshona Vafoyevna Respublic of Uzbekistan,Samarkand Assistant teacher of Samarkand institute of Economics and Service,Students of Samarkand institute of Economics and Service

Keywords:

AI-Based Fraud Detection, Digital Banking, Uzbekistan, Financial Crime, Machine Learning, Cybersecurity, Risk Management, Effectiveness Evaluation

Abstract

This study investigates the effectiveness of AI-based fraud detection systems within the digital banking sector of Uzbekistan between 2020 and 2025. It analyzes the performance metrics of these systems, including false positive rates, true positive rates, and overall fraud reduction, to assess their impact on financial security. The research employs a mixed-methods approach, combining quantitative data from banking institutions with qualitative insights from industry experts. Findings aim to provide valuable insights for policymakers, financial institutions, and technology developers seeking to enhance fraud prevention strategies in emerging digital economies. Ultimately, this paper contributes to understanding the practical application and efficacy of AI in combating financial crime in a specific regional context.

References

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O‘zbekiston Respublikasi Markaziybanki (2024)