Based On Bank Credit Risk Management Of AL-VaR Metrics Model Research

Since2007the US subprime crisis, both the industry and the authorities have putthe assessment and management of credit risk in the first place, credit risk has becomeone of the most concerned problems for financial institutions and supervisiondepartments. In such a financial background, to understand the history and trends incredit risk measurement methods, learn from the world’s advanced credit riskmeasurement methods to effectively prevent risks, particularly credit risk, willbecome one of the major issues and problems facing the banking industry. Forresearch and development credit risk measurement method is suitable for China’snational conditions, to improve credit risk management banks and other financialinstitutions, has important theoretical and practical significance.This Thesis based on the survey of risk management status of China’scommercial bank credit, combined with the actual situation of the bank’s credit riskmanagement, the introduction of Credit Metrics model based on VaR approach incredit risk metrics, and on the VaR method to optimize the introduction of asymmetricLaplace distribution, with asymmetric Laplace distribution VaR to quantify andrepresent risk constructed Credit Metrics model based on asymmetric Laplacedistribution VaR. And by asymmetric Laplace distribution VaR of Credit Metricsmodel in a number of key issues for empirical research, the application of this modelof commercial bank credit risk management ideas for China’s commercial banks toimprove credit risk management has some practical significance.