Open Access
The Trajectory of Ai-Driven Credit Scoring and The Refinement of Legal Mechanisms for A Digital Future: Tort Disputes and Liability
Amirjon Mardonov
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,
,
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Lecturer, Cyber Law Department, Tashkent State University of Law, Uzbekistan
Abstract
This paper examines the nature of extra-contractual (tort) harm inflicted on consumers within the financial sector as a consequence of artificial intelligence (AI) deployment in creditworthiness assessments. It investigates the foundational challenges of liability attribution, burden of proof, and algorithmic opacity through comparative analysis of civil legislation of the Republic of Uzbekistan, international regulatory frameworks (EU, US, Singapore, UK, China), and prevailing scholarly debate. Drawing on the positions of both international scholars — Selbst, Wendehorst, Rudin, Floridi — and Uzbek researchers — Tadjiev, Usmanov, Mukhtorov — the article proposes targeted reforms: a rebuttable presumption of causality, mandatory algorithmic explainability standards, and a graduated strict liability regime for high-risk AI systems in consumer finance. The overarching aim is to reconcile banking sector innovation with the inviolable procedural rights of the individual borrower.
Keywords
Tort obligations,
artificial intelligence,
credit scoring
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How to Cite
The Trajectory of Ai-Driven Credit Scoring and The Refinement of Legal Mechanisms for A Digital Future: Tort Disputes and Liability. (2026). Global Journal of Humanities and Social Sciences, 5(03), 1-8. https://doi.org/10.55640/gjhss/Volume05Issue03-01
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