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

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 th

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CreatorUrozova Nigora Toshmurodovna
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Published2026-04-22
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DOI10.5281/zenodo.19693800
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Downloads39
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Licensecc-by-4.0
File Size172.2 KB
Data TypeDataset
Published2026
Licensecc-by-4.0
Total Views81
Total Downloads39

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.

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EVALUATING THE EFFECTIVENESS OF AI-BASED FRAUD DETECTION IN… (Full Dataset)172.2 KB
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Files are hosted on the source repository. Click download to access the full dataset.

Urozova Nigora Toshmurodovna (2026). EVALUATING THE EFFECTIVENESS OF AI-BASED FRAUD DETECTION IN DIGITAL BANKING: EVIDENCE FROM UZBEKISTAN (2020–2025). https://doi.org/10.5281/zenodo.19693800