Commercial Bank Credit Risk Assessment Based On Fisher-KMV Model

In fact, the operation of modern commercial banks is based on credit. How to managethe credit risk of banks effectively is the most important issue that commercial banks face.Our financial market and banks are on the stage of shunt and emerging development, socredit risk management techniques fall behind. Now in our country the credit system’sbuilding is in start stage, we are lack of effective and viable methods to collect andintegrate credit risk. So in accordance with our country’s physical truth, it has veryimportant theory and reality meanings to develop credit risk management methodsaccording to information and resources we own now.At present, the usual methods that used in credit risk assessment in internationalinclude conditional credit risk assessment methods and modern credit risk assessmentmethods. The conditional credit risk assessment methods is familiar to handicraftworkshop having poor efficiency and high cost. They mainly depend on subjectivejudgment and historical data，so they have the character of backward-looking. Moderncredit risk assessment methods use engineering thinking and programming technology, andthe method has the character of forward-looking.. And the trend of engineering is more andmore obvious. Now in our country, the popular credit risk assessment methods includeexpects method and discriminant method of multiple which belongs to conditional creditrisk assessment method.At first, this paper introduce the basic theory of credit risk, and then analogy theconditional and modern credit risk assessment methods, compare the strength andweakness of the models, in further bring up the issues in our county’s credit riskmanagement. The papers about commercial banks’ credit risk assessment mainly usehistorical data to build models, so the results of the model must be lagging. And we haveso many improvements in KMV model, but every method has its weakness, and there arehardly researches that can merge them together. In this situation, this paper merges thefinancial ratios and stock market data together in empirical part. The KMV model’s resultDD is thought as a variable brought into Fisher model, and at last, we use total sample and test sample to test the model’s efficiency. The result suggests that the improved model canbe both reflect the companies’ financial situation and reflect the reality market situation,and then improve the accuracy of commercial banks’ prediction of credit risk.In the last part of this paper, some suggestion and some weaknesses of theFisher-KMV model are brought up. Banks should think risk as their resources form whichexplore their developing room.