LEGAL MECHANISMS FOR RISK MANAGEMENT WHEN USING ARTIFICIAL INTELLIGENCE IN THE BANK SCORING SYSTEM
DOI:
https://doi.org/10.47390/SPR1342V5SI4Y2025N31Keywords:
artificial intelligence, credit scoring, algorithmic risk, discrimination, transparency, regulation and personal data.Abstract
The article examines legal mechanisms for risk management when implementing artificial intelligence (AI) systems in banking scoring. International standards and approaches are analyzed - GDPR, the draft EU AI Act, ISO/IEC 23894:2023 - as well as the legislation of the Republic of Uzbekistan (Law on Personal Data, AI Development Strategy until 2030, etc.). Based on a comparative analysis and case study (Apple Card in the USA, SCHUFA in Germany, Asia Alliance Bank in Uzbekistan), the key risks of using AI in credit scoring are identified: discrimination, lack of transparency of algorithms, violation of consumer rights and inadequacy of models. Existing legal measures to minimize these risks are considered, such as requirements to prevent algorithmic discrimination, ensuring transparency and explainability of decisions, protecting personal data and the rights of consumers to appeal automated decisions. The discussion section offers recommendations for improving the regulation of AI use in banking lending in Uzbekistan, taking into account international experience - including the development of special regulations on high-risk AI systems, mandatory risk assessments and algorithm audits, and increased oversight of compliance with the principles of fairness and transparency. The implementation of these measures will reduce the likelihood of algorithmic errors and abuses, increase the level of trust in AI systems in the financial sector, and ensure a balance between innovation and the protection of citizens' rights.
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