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Nicholas S. Souleles - One of the best experts on this subject based on the ideXlab platform.
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benefits of relationship banking evidence from Consumer Credit markets
2018Co-Authors: Sumit Agarwal, Souphala Chomsisengphet, Chunlin Liu, Changcheng Song, Nicholas S. SoulelesAbstract:Abstract Using a unique panel dataset that contains comprehensive information about the relationships between a large bank and its Credit card customers, we show that relationship accounts exhibit lower probabilities of default and attrition, and have higher utilization rates, than non-relationship accounts. Dynamic information about changes in the behavior of a customer's other accounts at the same bank helps predict the behavior of the Credit card account over time. These results imply that relationship banking offers significant potential benefits to banks: information the lender has at its disposal can be used to mitigate Credit risk on the Credit card account.
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benefits of relationship banking evidence from Consumer Credit markets
2009Co-Authors: Sumit Agarwal, Nicholas S. Souleles, Souphala Chomsisengphet, Chunlin Liu, Changcheng SongAbstract:This paper empirically examines the benefits of relationship banking to banks, in the context of Consumer Credit markets. Using a unique panel dataset that contains comprehensive information about the relationships between a large bank and its Credit card customers, we estimate the effects of relationship banking on the customers’ default, attrition, and utilization behavior. We find that relationship accounts exhibit lower probabilities of default and attrition, and have higher utilization rates, compared to non-relationship accounts, ceteris paribus. Such effects become more pronounced with increases in various measures of the strength of the relationships, such as relationship breadth, depth, length, and proximity. Moreover, dynamic information about changes in the behavior of a customer’s other accounts at the bank, such as changes in checking and savings balances, helps predict and thus monitor the behavior of the Credit card account over time. These results imply significant potential benefits of relationship banking to banks in the retail Credit market.
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a portfolio view of Consumer Credit
2005Co-Authors: David K. Musto, Nicholas S. SoulelesAbstract:Abstract To compute risk-adjusted returns and gauge the volatility of their portfolios, lenders need to know the covariances of their loans’ returns with aggregate returns. We use unique Credit bureau data to measure individuals’ ‘covariance risk’, i.e., the covariance of their default risk with aggregate Consumer default rates, and more generally to analyze the distribution of Credit, including the effects of Credit scores. We find significant heterogeneity in covariance risk across Consumers. Also, the amount of Credit they obtain significantly increases with their Credit scores, and decreases with their covariance risk (especially revolving Credit), though the effect of covariance risk is smaller.
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A Portfolio View of Consumer Credit
2005Co-Authors: David K. Musto, Nicholas S. SoulelesAbstract:To compute risk-adjusted returns and gauge the volatility of their portfolios, lenders need to know the covariances of their loans' returns with aggregate returns. Cross-sectional differences in these covariances also provide insight into the nature of the shocks hitting different types of Consumers. We use a unique panel dataset of Credit bureau records to measure the 'covariance risk' of individual Consumers, i.e., the covariance of their default risk with aggregate Consumer default rates, and more generally to analyze the cross-sectional distribution of Credit, including the effects of Credit scores. We obtain two key sets of results. First, there is significant systematic heterogeneity in covariance risk across Consumers with different characteristics. Consumers with high covariance risk tend to also have low Credit scores (high default probabilities). Second, the amount of Credit obtained by Consumers significantly increases with their Credit scores, and significantly decreases with their covariance risk (especially revolving Credit), though the effect of covariance risk is smaller in magnitude.
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a portfolio view of Consumer Credit
2005Co-Authors: David K. Musto, Nicholas S. SoulelesAbstract:This paper takes a portfolio view of Consumer Credit. Default models (Credit-risk scores) estimate the probability of default of individual loans. But to compute risk-adjusted returns, lenders also need to know the covariances of the returns on their loans with aggregate returns. Covariances are independently relevant for lenders who care directly about the volatility of their portfolios, e.g., because of Value-at-Risk considerations or the structure of the securitization market. Cross-sectional differences in these covariances also provide insight into the nature of the shocks hitting different types of Consumers. We use a unique panel dataset of Credit bureau records to measure the "covariance risk" of individual Consumers, i.e., the covariance of their default risk with aggregate Consumer default rates, and more generally to analyze the cross-sectional distribution of Credit, including the effects of Credit scores. We obtain two key sets of results. First, there is significant systematic heterogeneity in covariance risk across Consumers with different characteristics. Consumers with high covariance risk tend to also have low Credit scores (high default probabilities). Second, the amount of Credit obtained by Consumers significantly increases with their Credit scores, and significantly decreases with their covariance risk (especially revolving Credit), though the effect of covariance risk is smaller in magnitude. It appears that some lenders take covariance risk into account, at least in part, in determining the amount of Credit they provide.
Guglielmo Weber - One of the best experts on this subject based on the ideXlab platform.
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Consumer Credit evidence from italian micro data
2005Co-Authors: Rob Alessie, Stefan Hochguertel, Guglielmo WeberAbstract:In this paper we analyse unique data on Credit applications received by the leading provider of Consumer Credit in Italy (Findomestic). The data set covers a five-year period (1995-1999) during which the Consumer Credit market rapidly expanded in Italy and a new law (the usury law) came into force that set a limit on interest rates charged to Consumers. We compute behavioural changes by controlling for changes in the observable characteristics of the Findomestic clientele and argue that, under suitable identifying assumptions, these changes can be given a structural interpretation. If the usury shock is assumed to have affected Credit supply but not Credit demand-that is, if the usury law had a differential impact on the supply of various types of Credit but a uniform impact on demand-then we can identify and estimate a demand equation. Our key finding is that demand is interest-rate elastic, particularly in the more affluent North. © 2005 by the European Economic Association.
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Consumer Credit evidence from italian micro data
2001Co-Authors: Rob Alessie, Stefan Hochguertel, Guglielmo WeberAbstract:In this Paper we analyse unique data on Credit applications received by the leading provider of Consumer Credit in Italy (Findomestic). The data set covers a five year period (1995-99) during which the Consumer Credit market rapidly expanded in Italy and a new law came into force that set a limit to interest rates charged to Consumers (the usury law). We investigate ways in which the law may have affected the Consumer Credit market and show how the applicants' pool has changed over time in comparison to a representative sample of the Italian population. We compute behavioural changes by controlling for changes in the observable characteristics of the Findomestic clientele and argue that, under suitable identifying assumptions, these changes can be given a structural interpretation. If the usury shock is assumed to have affected Credit supply but not Credit demand, that is if the usury law had a differential impact on the supply of various types of Credit but a uniform impact on demand, we can identify and estimate a demand equation. Our key finding is that demand is interest rate elastic, particularly in the North, where the Consumer Credit market is more competitive.
Sumit Agarwal - One of the best experts on this subject based on the ideXlab platform.
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disguised corruption evidence from Consumer Credit in china
2020Co-Authors: Sumit Agarwal, Wenlan Qian, Amit Seru, Jian ZhangAbstract:Abstract Using a comprehensive sample of Credit card data from a leading Chinese bank, we show that government bureaucrats receive 16% higher Credit lines than non-bureaucrats with similar income and demographics, but their accounts experience a significantly higher likelihood of delinquency and debt forgiveness. Regions associated with greater Credit provision to bureaucrats open more branches and receive more deposits from the local government. After staggered corruption crackdowns of provincial-level political officials, the new Credit cards originated to bureaucrats in exposed regions do not enjoy a Credit line premium, and bureaucrats’ delinquency and reinstatement rates are similar to those of non-bureaucrats.
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disguised corruption evidence from Consumer Credit in china
2018Co-Authors: Sumit Agarwal, Wenlan Qian, Amit Seru, Jian ZhangAbstract:Using a comprehensive sample of Credit card data from a leading Chinese bank, we find that government bureaucrats receive 16% higher Credit lines than non-bureaucrats with similar income and demographics, but their accounts experience a significantly higher likelihood of delinquency and debt forgiveness. These patterns are concentrated among bureaucrats with greater power and located in more “corrupt” cities. Areas associated with greater Credit provision to bureaucrats open more branches and receive more deposits from the local government. Using staggered crackdowns of provincial-level political officials as exogenous shocks to the risk of corruption investigation, we find that the new Credit cards originated to bureaucrats do not enjoy a Credit line premium, and bureaucrats’ delinquency and reinstatement rates are no higher than those of non-bureaucrats in the treated provinces during the post-crackdown period. We use our estimates to infer the size of corruption and explore the impact on aggregate economic outcomes.
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benefits of relationship banking evidence from Consumer Credit markets
2018Co-Authors: Sumit Agarwal, Souphala Chomsisengphet, Chunlin Liu, Changcheng Song, Nicholas S. SoulelesAbstract:Abstract Using a unique panel dataset that contains comprehensive information about the relationships between a large bank and its Credit card customers, we show that relationship accounts exhibit lower probabilities of default and attrition, and have higher utilization rates, than non-relationship accounts. Dynamic information about changes in the behavior of a customer's other accounts at the same bank helps predict the behavior of the Credit card account over time. These results imply that relationship banking offers significant potential benefits to banks: information the lender has at its disposal can be used to mitigate Credit risk on the Credit card account.
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benefits of relationship banking evidence from Consumer Credit markets
2009Co-Authors: Sumit Agarwal, Nicholas S. Souleles, Souphala Chomsisengphet, Chunlin Liu, Changcheng SongAbstract:This paper empirically examines the benefits of relationship banking to banks, in the context of Consumer Credit markets. Using a unique panel dataset that contains comprehensive information about the relationships between a large bank and its Credit card customers, we estimate the effects of relationship banking on the customers’ default, attrition, and utilization behavior. We find that relationship accounts exhibit lower probabilities of default and attrition, and have higher utilization rates, compared to non-relationship accounts, ceteris paribus. Such effects become more pronounced with increases in various measures of the strength of the relationships, such as relationship breadth, depth, length, and proximity. Moreover, dynamic information about changes in the behavior of a customer’s other accounts at the bank, such as changes in checking and savings balances, helps predict and thus monitor the behavior of the Credit card account over time. These results imply significant potential benefits of relationship banking to banks in the retail Credit market.
Francis A Longstaff - One of the best experts on this subject based on the ideXlab platform.
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the market risk premium for unsecured Consumer Credit risk
2020Co-Authors: Matthias Fleckenstein, Francis A LongstaffAbstract:We use the prices of Credit card asset-backed securities to study the market risk premium associated with unsecured Consumer Credit risk. The Consumer Credit risk premium has historically been comparable to high yield corporate bond spreads, but has increased dramatically since the financial crisis. We find evidence that this increase is primarily due to balance-sheet costs imposed by recent changes in regulatory capital requirements which have effectively placed Credit card securitizations back onto issuer balance sheets. These changes in capital regulation may have added hundreds of basis points to the cost of unsecured household Credit.
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the market risk premium for unsecured Consumer Credit risk
2020Co-Authors: Matthias Fleckenstein, Francis A LongstaffAbstract:We use the prices of Credit card asset-backed securities to study the market risk premium associated with unsecured Consumer Credit risk. The Consumer Credit risk premium has historically been comparable to high yield corporate bond spreads, but has increased dramatically since the financial crisis. We find evidence that this increase is primarily due to balance-sheet costs imposed by recent changes in regulatory capital requirements which have effectively placed Credit card securitizations back onto issuer balance sheets. These changes in capital regulation may have added hundreds of basis points to the cost of unsecured household Credit. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.
Lyn C Thomas - One of the best experts on this subject based on the ideXlab platform.
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transition matrix models of Consumer Credit ratings
2012Co-Authors: Madhur Malik, Lyn C ThomasAbstract:Abstract 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.
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transition matrix models of Consumer Credit ratings
2010Co-Authors: Madhur Malik, Lyn C ThomasAbstract:The corporate Credit risk literature has many studies modelling the change in the Credit risk of corporate bonds over time. There is far less analysis of the Credit risk for portfolios of Consumer loans. However behavioural scores, which are commonly calculated on a monthly basis by most Consumer lenders are the analogues of ratings in corporate Credit risk. Motivated by studies in corporate Credit risk, we develop a Markov chain model based on behavioural scores to establish the Credit risk of portfolios of Consumer loans. However such a Consumer Credit model differs in many respects from corporate Credit ones based on Markov chains – 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.
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Consumer Credit models pricing profit and portfolios
2009Co-Authors: Lyn C ThomasAbstract:The use of Credit scoring - the quantitative and statistical techniques to assess the Credit risks involved in lending to Consumers - has been one of the most successful if unsung applications of mathematics in business for the last fifty years. Now with lenders changing their objectives from minimising defaults to maximising profits, the saturation of the Consumer Credit market allowing borrowers to be more discriminating in their choice of which loans, mortgages and Credit cards to use, and the Basel Accord banking regulations raising the profile of Credit scoring within banks there are a number of challenges that require new models that use Credit scores as inputs and extensions of the ideas in Credit scoring. This book reviews the current methodology and measures used in Credit scoring and then looks at the models that can be used to address these new challenges. The first chapter describes what a Credit score is and how a scorecard is built which gives Credit scores and models how the score is used in the lending decision. The second chapter describes the different ways the quality of a scorecard can be measured and points out how some of these measure the discrimination of the score, some the probability prediction of the score, and some the categorical predictions that are made using the score. The remaining three chapters address how to use risk and response scoring to model the new problems in Consumer lending. Chapter three looks at models that assist in deciding how to vary the loan terms made to different potential borrowers depending on their individual characteristics. Risk based pricing is the most common approach being introduced. Chapter four describes how one can use Markov chains and survival analysis to model the dynamics of a borrower's repayment and ordering behaviour . These models allow one to make decisions that maximise the profitability of the borrower to the lender and can be considered as part of a customer relationship management strategy. The last chapter looks at how the new banking regulations in the Basel Accord apply to Consumer lending. It develops models that show how they will change the operating decisions used in Consumer lending and how their need for stress testing requires the development of new models to assess the Credit risk of portfolios of Consumer loans rather than a models of the Credit risks of individual loans.
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recent developments in Consumer Credit risk assessment
2007Co-Authors: Jonathan Crook, David B Edelman, Lyn C ThomasAbstract:Consumer Credit risk assessment involves the use of risk assessment tools to manage a borrower’s account from the time of pre-screening a potential application through to the management of the account during its life and possible write-off. The riskiness of lending to a Credit applicant is usually estimated using a logistic regression model though researchers have considered many other types of classifier and whilst preliminary evidence suggest support vector machines seem to be the most accurate, data quality issues may prevent these laboratory based results from being achieved in practice. The training of a classifier on a sample of accepted applicants rather than on a sample representative of the applicant population seems not to result in bias though it does result in difficulties in setting the cut off. Profit scoring is a promising line of research and the Basel 2 accord has had profound implications for the way in which Credit applicants are assessed and bank policies adopted.
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A survey of the issues in Consumer Credit modelling research
2005Co-Authors: Lyn C Thomas, R W Oliver, D J HandAbstract:Methods for assessing the Credit risk when lending to Consumers has been in operation for 50 years. Yet, there are probably now more opportunities and challenges for research into the development of this area than ever before. This paper surveys the development of the methodology, describes the current environment for Consumer lending and seeks to identify some of the modelling areas and issues that are actively being researched or should be.