Transition matrix models of consumer credit ratings

Although the corporate credit risk literature includes many studies modelling the change in the credit risk of corporate bonds over time, there has been far less analysis of the credit risk for portfolios of consumer loans. However, behavioural scores, which are calculated on a monthly basis by most consumer lenders, are the analogues of ratings in corporate credit risk. Motivated by studies of corporate credit risk, we develop a Markov chain model based on behavioural scores for establishing the credit risk of portfolios of consumer loans. Although such models have been used by lenders to develop models for the Basel Accord, nothing has been published in the literature on them. The model which we suggest differs in many respects from the corporate credit ones based on Markov chains — such as the need for a second order Markov chain, the inclusion of economic variables and the age of the loan. The model is applied using data on a credit card portfolio from a major UK bank.     

A Cost System Approach to the Stochastic Directional Technology Distance Function with Undesirable Outputs: The Case of us Banks in 2001–2010

This paper offers a methodology to address the endogeneity of inputs in the directional technology distance function (DTDF)‐based formulation of banking technology which explicitly accommodates the presence of undesirable nonperforming loans—an inherent characteristic of the bank's production due to its exposure to credit risk. Specifically, we model nonperforming loans as an undesirable output in the bank's production process. Since the stochastic DTDF describing banking technology is likely to suffer from the endogeneity of inputs, we propose addressing this problem by considering a system consisting of the DTDF and the first‐order conditions from the bank's cost minimization problem. The first‐order conditions also allow us to identify the ‘cost‐optimal’ directional vector for the banking DTDF, thus eliminating the uncertainty associated with an ad hoc choice of the direction. We apply our cost system approach to the data on large US commercial banks for the 2001–2010 period, which we estimate via Bayesian Markov chain Monte Carlo methods subject to theoretical regularity conditions. We document dramatic distortions in banks' efficiency, productivity growth and scale elasticity estimates when the endogeneity of inputs is assumed away and/or the DTDF is fitted in an arbitrary direction. Copyright © 2015 John Wiley & Sons, Ltd.     

Default risk and private student loans: Implications for higher education policies

In recent years, the proportion of students facing a binding constraint on government student loans has grown. This has led to substantially increased use of private loans as a supplementary source of finance for households׳ higher education investment. A critical aspect of the private market for student loans is that loan terms must reflect students׳ risk of default. College investment will therefore differ from a world in which government student loans, whose terms are not sensitive to credit risk, are expanded to no longer bind. Moreover, beyond simply crowding out private lending, expansions of the government student loan program will feed back into default risk on private loans. The goal of this paper is to provide a quantitative assessment of the likely effects of the private market for student loans on college enrollment. We build a model of college investment that reflects uninsured idiosyncratic risk and a well-defined life-cycle that is consistent with observed borrowing and default behavior across family income and college preparedness. We find that higher government borrowing limits increase college investment but lead to more default in the private market for student loans, while tuition subsides increase college investment and reduce default rates in the private market. Consequently, higher limits on government student loans have small negative welfare effects, while tuition subsidies increase aggregate welfare.     

The interest rate spreads in the Czech Republic: Different loans,different determinants?

We analyze the determinants of interest rate spreads of different loan categories in the Czech Republic during 2004–2011. We employ a detailed bank supervisory dataset that allows us to construct the actual spreads for four loan categories, namely small and large corporate loans, consumer loans and mortgages, on a monthly basis. Our regression analysis shows that bank and macroeconomic characteristics matter more for setting the spreads for small corporate loans and mortgages rather than for large corporate loans and consumer loans. Interest rate risk determines the spreads for all loan categories. The global financial crisis has, to a certain extent, increased the responsiveness of spreads to interest rate risk and liquidity risk.     

Forecasting and decomposition of portfolio credit risk using macroeconomic and frailty factors

This paper presents a dynamic portfolio credit model following the regulatory framework, using macroeconomic and latent risk factors to predict the aggregate loan portfolio loss in a banking system. The latent risk factors have three levels: global across the entire banking system, parent-sectoral for the intermediate loan sectors and sector-specific for the individual loan sectors. The aggregate credit loss distribution of the banking system over a risk horizon is generated by Monte Carlo simulation, and a quantile estimator is used to produce the aggregate risk measure and economic capital. The risk contributions of the individual sectors and risk factors are measured by combining the Hoeffding decomposition with the Euler capital allocation rule. For the U.S. banking system, we find that the real GDP growth rate, the global and sector-wide frailty risk factors and their spillovers significantly affect loan defaults, and the impacts of the frailty factors are not only economy-wide but also sector-specific. We also find that the frailty risk factors make more significant risk contributions to the aggregate portfolio risk than the macroeconomic factors, while the macroeconomic factors help to improve the accuracy and efficiency of the credit risk forecasts.     

An asset protection scheme for banks exposed to troubled loan portfolios

We examine a specific portfolio credit derivative, an Asset Protection Scheme (APS), and its applicability as a discretionary regulatory tool to reduce asymmetric information and help restore the capital base of troubled banks. The APS can be a fair-valued contract with an appropriate structure of incentives. We apply two alternative multivariate structural default risk models: the classical Gaussian Merton model and a model based on Normal Inverse Gaussian processes. Using a data set on annual farm level data from 1996 to 2009, we use the Danish agricultural sector as a case study and price an APS on an agricultural loan portfolio. We compute the economic capital for this loan portfolio with and without an APS. Moreover, we illustrate how model risk in the form of parameter uncertainty is reduced when an APS is attached to the loan portfolio.     

Bank lending rules for managing sovereign risk

A simple domestic lending rule is one that ensures that the loan rate exceeds the bank's cost of capital and the borrower's expected cashflows exceed the terminal value of the loan. Because a sovereign loan is not collateralized and lacks recourse, the domestic lending rule is not adequate for making sovereign lending decisions. Three modifications are suggested. First, the sovereign borrower's time preference for consumption needs to be considered. Second, the domestic borrower's decision to default voluntarily is made after observing the value of the collateral whereas the sovereign borrower's decision is made after observing earnings. In this paper, the sovereign borrower upgrades expectations in a Bayesian manner. Although no lending rule will completely prevent a default, the probability of default can be managed leading to a third modification.     

基于高阶矩风险防范的银行资产负债组合优化模型研究——以A银行为例

资产负债管理能力是现代商业银行的基本能力,其核心在于风险控制和价值创造。商业银行资产负债组合优化是现代商业银行信贷管理框架中的核心内容,它对于保持银行资产流动性、安全性和赢利性的＂三性＂的最佳组合、优化配置资源、提高银行的生存能力和竞争能力,具有重要的现实意义。本文通过以贷款组合的VaR约束控制贷款组合的二阶矩,即控制了资产组合的风险;以贷款组合收益率的偏度约束控制贷款组合的三阶矩,即控制了贷款组合收益率发生总体损失的可能性;以组合收益率的峰度约束控制贷款组合的四阶矩,即减少了组合收益率发生极端损失的可能性,建立了资产分配的收益率均值-方差-偏度-峰度模型。     

Form of ownership and risk taking in banking: Some evidence from Massachusetts savings banks

In recent years there has been interest in the impact of the form of ownership on the behavior of financial institutions. In the 1980’s, there was a substantial movement away from mutual ownership to stock ownership in the thrift industry. The effect of this conversion process on risk taking and efficiency has been a matter of concern. The purpose of this paper is to examine the experience of savings banks in Massachusetts. A panel of 115 savings banks is analyzed for the years 1985 through 1993, a period that includes both rapid growth and a subsequent severe cyclical decline in property values. The credit quality of loan portfolios is related to the size of the portfolio, the structure of the portfolio, and the ownership status of the bank. Several models are estimated. In all cases, it was found that the cyclical decline in property values resulted in a decline in the credit quality of loan portfolios with a substantially greater impact on those savings banks that converted from mutual to stock status.     

Stability in consumer credit scores: Level and direction of FICO score drift as a precursor to mortgage default and prepayment

This article represents an extension of the expansive credit risk and credit migration literature, prominent in the corporate bond and securities risk pricing literature, to an analysis of the drift of consumer credit scores. A rich data set of residential mortgages is used to observe credit score migration post loan origination and in a test of the ability of credit score transition to serve as a precursor to potential default and prepayment. The results indicate credit scores provide signals and information to investors and servicing agents in a fashion similar to credit ratings on commercial paper as to default potential.     

Financial fragility,uninsured deposits,and the cost of debt

Using annual data from 1995 to 2009, I analyze the impact of banks’ financial fragility on the costs of U.S. corporate bank loans. Diamond and Rajan (2001) hypothesize that financially fragile banks are able to raise funds at a lower cost and competition among banks result in some of these benefits being passed on to borrowers. My results provide broad support for this hypothesis, as I find that a one standard deviation increase in a bank's financial fragility lowers the cost of this bank's corporate loans by 7%. Since some types of regulation, such as deposit insurance, can decrease banks’ financial fragility, this paper also contributes to the debate on the benefits and costs of bank regulation which can be helpful for policy-making.     

A through-the-cycle model for retail lending economic capital

Problems in the US mortgage industry have shown weaknesses in the standard regulatory and economic capital approaches. Although a significant amount of discussion is occurring around how to segment portfolios or predict key variables in order to better fit the existing formulas, we believe that a re-examination of existing capital formulas with respect to credit risk is required.In this paper we develop a formula which is specifically tuned to the dynamics of retail loan portfolios and which could be employed for either regulatory capital or economic capital. The key advantages of this approach are that it is based upon a much more accurate model of retail loan defaults, does not require any new data feeds, is based upon readily available modeling frameworks, and can adapt to portfolio changes such as those observed in the US mortgage crisis.     

Cyclicality in losses on bank loans

Based on unique data we show that macro variables, the default rate and loss given default of bank loans share common cyclical components. The innovation in our model is the distinction between loans with either severe or mild losses. The variation in the proportion of these two types drives the cyclic behavior of the loss given default and constitutes the links with the default rate and macro variables. These links vary according to loan and borrower characteristics. During downturns, the proportion of defaults with severe losses increases, but the distribution of losses conditional on their being mild or severe does not change. although loans are monitored more closely than bonds and are more senior, the cyclical variation in their losses resembles those for bonds, albeit around a lower average level. This variation leads to an increase in the capital reserves required for loan portfolios.     

Spatial dependence in microfinance credit default

Credit scoring model development is very important for the lending decisions of financial institutions. The creditworthiness of borrowers is evaluated by assessing their hard and soft information. However, microfinance borrowers are very sensitive to a local economic downturn and extreme (weather or climate) events. Therefore, this paper is devoted to extending the standard credit scoring models by taking into account the spatial dependence in credit risk. We estimate a credit scoring model with spatial random effects using the distance matrix based on the borrowers’ locations. We find that including the spatial random effects improves the ability to predict defaults and non-defaults of both individual and group loans. Furthermore, we find that several loan characteristics and demographic information are important determinants of individual loan default but not group loans. Our study provides valuable insights for professionals and academics in credit scoring for microfinance and rural finance.     

银行不良贷款违约损失率结构特征研究

本文对中国银行业面临的信用风险违约损失率(LGD)展开研究,以温州某商业银行不良贷款数据为样本,通过描述性统计,对LGD的结构特征:信用风险暴露规模特征、期限特征、地域特征以及担保特征等进行了详细分析。结果表明LGD与风险暴露规模呈负相关,LGD与贷款期限呈正相关,不同地域、不同担保方式的违约贷款其LGD差异性显著。以上这些结论可为商业银行信用风险管理、信贷投放导向以及信用风险监管提供现实帮助。     

Premia for correlated default risk

Using data on corporate default experience in the U.S. and market rates of CDX index and tranche swaps of various maturities, we estimate reduced-form models of correlated default timing in the CDX High Yield and Investment Grade portfolios under actual and risk-neutral probabilities. The striking contrast between the estimated processes followed by the actual and risk-neutral arrival intensities of defaults, and between the parameters governing the actual and risk-neutral dynamics of the risk-neutral intensities, indicates the presence of substantial default risk premia in CDX swap market rates. The effects of risk premia on swap rates covary strongly across maturities, and depend on general stock market volatility and several measures of credit spreads. Large moves in the effects of these premia on swap rates have natural interpretations in terms of economic and financial market developments during the sample period, April 2004 to October 2007. Our results suggest that a large portion of the movements in CDX swap market rates observed during the sample period may be caused by changing attitudes toward correlated default risk rather than changes in the economic factors affecting the actual risk of clustered defaults, which ultimately governs swap payoffs.     

Commercial mortgage underwriting: How well do lenders manage the risks?

Loan-to-value ratio and debt service coverage ratios have long been viewed as the two most important quantitative measures of the default risk of commercial mortgages. Option-based models of default provide strong theoretic support for the importance of original loan-to-value ratio. The same theoretical predictions have found strong empirical support in residential single-family mortgage analyses. However, recent empirical studies of commercial mortgage default have raised questions about the role of loan-to-value ratio in assessing the riskiness of commercial mortgages. These studies generally either find no relationship or a puzzling negative relationship between loan-to-value ratio and default. This paper uses a very large database of commercial loan histories to thoroughly investigate this issue. It finds strong evidence that loan-to-value and debt service coverage ratios are endogenous to the underwriting process. Lenders react to other—unmeasured—risk factors with credit rationing and pricing. As a result, unusually low loan-to-value ratio loans appear to have above average risk in other dimensions and their default probabilities are equal to or higher than average. The results show that the pricing spread that lenders establish as part of the underwriting process serves as an excellent summary measure of the riskiness of the loan. A test of lenders’ ability to appropriately price loan-to-value risk finds that, while there is some unpriced effect of loan-to-value ratio after controlling for the lender’s pricing, introducing lender pricing into the model removes the otherwise puzzling negative loan-to-value and default relationship previously observed in the literature.     

基于省域视角的信用风险模型适应性分析

巴塞尔新资本协议在鼓励银行采用内部评级法评估信用风险以提取资本准备的同时也强化了各国监管机构对内部评级模型绩效检验与审查的要求.CreditMetrics和CreditRisk+是银行业信用风险评估的基准模型.从建模的数学方法看,CreditRisk+是基于违约的判断,而CreditMetrics则是根据等级变化评价.利用江苏省银监局的相关统计数据对信用风险评估模型进行参数特性审查与绩效检验,结果显示这两类常用模型都可以在江苏的商业银行经营实践中稳定地实现根据信贷组合的实际风险状况进行内部资本配置这一目标.     

A novel profit cutting mechanism for Chinese Banks: Theory and Multi-dimensional evidence

As China’s macroeconomic growth faces increasing pressure from the global COVID-19 pandemic, a surprising and politically controversial phenomenon has emerged: the profitability of banks in China exceeded that of enterprises and non-financial industries. The People’s Bank of China and regulatory authorities have hence taken measures to incentivize banks to transfer part of their profits to enterprises, with the aim to stabilize enterprises and employment. This paper proposes a novel profit cutting mechanism focusing on loan structure adjustments to address the limitations of the current approach centering on lowering loan interest rates. The theoretical and empirical analysis show, at both the macro and micro level, that an increase in the proportion of credit loans can benefit the development of enterprises without weakening banks’ operating performance in the long term, leading to a Pareto improvement within enterprise-banking sectors. The findings suggest that banks in China should gradually adjust their loan structures by providing greater credit loan access to enterprises, either voluntarily or directed by policy.