Credit risk and derivatives in the banking sector

The banking sector plays a critical role as one of the most important components of the financial system, contributing significantly to economic stability and supporting development. However, one of the most significant challenges faced by banks is credit risk management. Credit risk refers to the potential losses a bank may encounter when a borrower fails to fulfill their obligations. This risk can directly affect the financial sustainability of banks and overall economic stability. In Turkey, the banking sector, particularly in terms of credit risk management, has undergone significant transformations in response to economic crises, evolving regulations, and advancing technologies. This study aims to provide a comprehensive examination of the academic research on credit risk management within the Turkish banking sector. It compiles key studies on the credit risk faced by banks in Turkey and discusses the impact of these studies on banking practices. Additionally, the study presents findings on how Turkey's economic conditions, regulatory interventions, and global financial crises have reflected on the credit risk strategies of banks. The study also addresses models that analyze the effects of macroeconomic factors on credit risk and how these factors influence the banking sector. The methods employed in credit risk management have undergone a significant transformation with the rise of advanced technologies. Findings suggest that credit assessment models based on artificial intelligence and machine learning provide more accurate and efficient results compared to traditional financial analysis methods. Furthermore, the study thoroughly examines the role and impact of regulations introduced by the Banking Regulation and Supervision Agency (BDDK) on the credit risk management processes of Turkish banks. These regulations have strengthened the credit vii risk management systems of banks, helping the sector become more resilient to financial crises. The study also aims to provide recommendations for the future direction of credit risk management in Turkey's banking sector, offering suggestions for sectoral improvements. Specifically, it discusses new opportunities and potential challenges regarding the role of emerging financial technologies, data analytics, and machine learning applications in credit risk management. In this context, the study highlights the structural and technological transformations required for enhancing the effectiveness of credit risk management strategies in Turkish banks. In conclusion, this study aims to contribute to the academic field by developing strategies and practices that can improve the efficiency and sustainability of credit risk management in the banking sector. Moreover, understanding how the challenges encountered in credit risk management shape the strategic decisions of banks is crucial from both academic and practical perspectives.