Harnessing Data and Technology for Effective Management of Non-Performing Loans: A Systematic Literature Review

This systematic literature review examines the role of emerging technologies, including artificial intelligence, machine learning, blockchain, cloud computing and data analytics, in enhancing the management of non-performing loans. Non-performing loans pose significant risks to financial stability and their effective management is crucial for maintaining the health of financial institutions. This study systematically synthesises existing research to identify how these technologies enhance non-performing loan processes, including identification, monitoring and recovery. The findings reveal that artificial intelligence and machine learning improve non-performing loan detection by analysing borrower behaviour, predicting default risks and enabling proactive risk management. Blockchain ensures secure and transparent loan records, enhancing data integrity and reducing fraud. Cloud computing and data analytics provide scalable solutions for continuous monitoring, while optimisation models and predictive analytics enhance recovery strategies. The review further highlights the influence of macroeconomic factors and bank-specific variables on non-performing loan levels, as well as how technology can mitigate these impacts. This research provides practical insights for financial institutions, regulators and technology providers, offering a roadmap for leveraging advanced technologies to enhance the efficiency of non-performing loan management and mitigate financial risks. Future research should expand its scope by incorporating multiple databases to gain a comprehensive understanding of global trends.