WAYS TO REDUCE PROBLEM LOANS OF COMMERCIAL BANKS IN THE DIGITAL ECONOMY.

Authors

  • Baymuratova Zina Aqilbekovna Author

Abstract

This article explores effective approaches to reducing problem loans in commercial banks within the context of the digital economy. The digital transformation of financial services introduces both opportunities and risks, requiring banks to adopt innovative risk management tools and data-driven decision-making models. The study highlights modern digital tools such as AI-based credit scoring, real-time transaction monitoring, and blockchain technology, evaluating their impact on credit risk mitigation. Recommendations for improving regulatory frameworks and customer transparency are also provided.

References

1. Smith, J., & Brown, L. (2020). Artificial Intelligence in Banking: A Revolution in Credit Risk Management. Journal of Financial Technology, 15(3), 223-245.

2. Taylor, M., & Green, R. (2019). Big Data Analytics and Its Role in Reducing Non-Performing Loans in Commercial Banks. International Journal of Banking and Finance, 42(1), 98-112.

3. Miller, P. (2021). Blockchain Technology: The Future of Credit Histories in the Digital Economy. Fintech Review, 8(4), 56-68.

4. Chen, X., & Zhao, Y. (2022). Machine Learning for Credit Scoring: Improving Accuracy and Reducing Risk in Lending. Journal of Applied Financial Technology, 29(2), 134-150.

5. Kumar, A., & Singh, S. (2021). The Role of Automated Loan Monitoring in Mitigating Credit Risk. Global Banking Review, 10(6), 210-228.

6. Patel, D., & Shah, K. (2020). The Impact of AI on Loan Default Prediction and Risk Mitigation Strategies. Banking Innovation Journal, 5(2), 77-90.

7. European Central Bank (2019). Regulatory Framework for the Use of Digital Technologies in Credit Risk Management. ECB Working Paper Series, No. 2356.

8. World Bank Group (2020). Digital Financial Services and Their Impact on Commercial Banking. Report on Financial Inclusion, 2019-2020.

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Published

2025-05-06