A new method to predict economic capital for the credit risk of a lending portfolio
提出一种不直接预测违约概率、而是通过建模借款人还款行为和余额来估算贷款组合在险价值的方法，发现该方法在某些情况下要求银行持有更多资本。
We propose a method to compute the Value at Risk for a loan portfolio that involves predicting outstanding balance and repayment amounts, but not the probability of default directly. By modelling the behaviour of the borrowers in terms of repayments, balance and a default condition, we model the default occurrence more accurately than if we model the occurrence of default directly. We find that whilst including random effects increases the predictive accuracy of individual account performances, relatively simple structures give the most accurate predictions. We also find that, in terms of value at risk relative to expected loss, more complex random effects predict lower values at risk at more distant duration times whilst the omission of random effects leads to increasing values at risk over time. We compare the predicted amount of capital a bank should hold under our approach and under a standard approach and find that under certain circumstances, our approach indicates that considerably more capital should be held.