Credit Risk Models Banks During the COVID-19 Pandemic
dc.contributor.advisor | Kyrychko, Yuliya | |
dc.contributor.author | Alakassi, Sattam | |
dc.date.accessioned | 2024-10-30T16:45:25Z | |
dc.date.issued | 2024 | |
dc.description.abstract | The COVID-19 pandemic has posed unprecedented challenges to the global financial system, particularly impacting credit risk management in banks. This dissertation explores the evolution of credit risk models and assessment techniques in banks during the COVID-19 pandemic. The study is motivated by the significant role credit risks play in the financial stability of banks and the broader economy, as well as the regulatory changes introduced to mitigate these risks. The research adopts a case study method, incorporating both qualitative and quantitative approaches. Qualitative data is gathered through semi-structured interviews with bank professionals and and analysis of regulatory reports and financial statements. Quantitative analysis is performed using statistical tools such as regression and time-series analysis to evaluate the effectiveness of credit risk models before and after the pandemic. | |
dc.format.extent | 41 | |
dc.identifier.uri | https://hdl.handle.net/20.500.14154/73412 | |
dc.language.iso | en | |
dc.publisher | University of Sussex | |
dc.subject | Risk management | |
dc.title | Credit Risk Models Banks During the COVID-19 Pandemic | |
dc.type | Thesis | |
sdl.degree.department | Department of Mathematics | |
sdl.degree.discipline | Financial risk management | |
sdl.degree.grantor | University of Sussex | |
sdl.degree.name | Corporate and Financial Risk Management |