Zugl.: Saarbrücken, Univ., Diss., 2007 / Includes bibliographical references (p. 257-272) and index.

This study attempts to present a brief survey of the major aspects of consumer credit in the United States today: credit institutions in general, co-operative and non cooperative consumer credit agencies, and the regulation of such agencies. A special chapter is devoted to consumer credit in Texas, with emphasis upon the fight which certain Texas cities are making against the loan-shark evil.

In these essays, I study how multidimensional private information causes advantageous selection in a highly concentrated consumer credit market. All three chapters are tightly correlated with each other. I first carefully investigate conditional correlations between choices of a loan type, private default risks, and an additional private information on consumption smoothing motives. I find that their conditional correlations appear consistent with advantageous selection being driven by unobserved heterogeneity in consumption smoothing motives. Then I document how moral hazard links two dimensions of private information: consumption smoothing motives and default risks. By separately identifying moral hazard from adverse selection, I show that consumers with stronger consumption smoothing motives exert more effort to prevent default, generating an endogenous negative association between consumption smoothing motives and default risks. Finally, using a dynamic model of loan type choices and following outcome of default, I recover the joint distribution of bi-dimensional unobserved heterogeneity. This structural estimation also suggests a new way to estimate the inter-temporal elasticity of substitution that represents heterogeneous consumption smoothing motives. As well as being consistent with the results of previous chapters, the results of the structural estimation reveal a strong and positive correlation between inter-temporal elasticity of substitution and default risks.

This thesis is concerned with statistical aspects of credit scoring, the process of determining how likely an applicant for credit is to default with repayments. In Chapters 1-4 a detailed introduction to credit scoring methodology is presented, including evaluation of previous published work on credit scoring and a review of discrimination and classification techniques. In Chapter 5 we describe different approaches to measuring the absolute and relative performance of credit scoring models. Two significance tests are proposed for comparing the bad rate amongst the accepts (or the error rate) from two classifiers. In Chapter 6 we consider different approaches to reject inference, the procedure of allocating class membership probabilities to the rejects. One reason for needing reject inference is to reduce the sample selection bias that results from using a sample consisting only of accepted applicants to build new scorecards. We show that the characteristic vectors for the rejects do not contain information about the parameters of the observed data likelihood, unless extra information or assumptions are included. Methods of reject inference which incorporate additional information are proposed. In Chapter 7 we make comparisons of a range of different parametric and nonparametric classification techniques for credit scoring: linear regression, logistic regression, projection pursuit regression, Poisson regression, decision trees and decision graphs. We conclude that classifier performance is fairly insensitive to the particular technique adopted. In Chapter 8 we describe the application of the k-NN method to credit scoring. We propose using an adjusted version of the Eucidean distance metric, which is designed to incorporate knowledge of class separation contained in the data. We evaluate properties of the k-NN classifier through empirical studies and make comparisons with existing techniques.

Ph.D. (Mathematical Statistics) / This thesis considers the modelling and prediction of consumer credit risk events. We model consumer credit risk events (like a missed payment, a repayment or a default) by means of a discrete, real time, staggered entry counting process. Merton s (1974) structural approach is the foundation of numerous credit-risk models, as well as the Basel capital accords. The underlying assumptions of this approach are that both liability and asset levels are observable to some extent and that default, which occurs if liability levels are larger than asset levels, can occur only once. These assumptions are inappropriate for consumer credit risk, where asset and liability levels are not observable and multiple defaults may occur. We nd that the so-called reduced-form models initially developed by Artzner and Delbaen (1995) and Jarrow and Turnbull (1995), which impose no structure on the default event, are better suited to model and predict consumer credit risk. All reduced-form models can be represented as counting processes. Counting processes are continuous in nature, so we discretize these processes before applying them to the regularly spaced, discrete monthly data. We show that the use of survival analysis tech- niques such as Cox s (1972) proportional hazard model, which is a special case in counting processes, are not well suited to model credit risk. This is because survival analysis is mostly concerned with the prediction of the time until a single event occurs. Accordingly, in survival analysis the time domain used is event time . Hence, all observations need to be aligned to some starting time. We prefer to work in calendar time and are concerned with the timing (in calendar time) of multiple events. We identify and implement a dynamic, discrete statistical model based on calendar time that accounts for staggered entries, multiple entries into and exits from the portfolio, as well as multiple default events on an account level. This approach, from Arjas and Haara (1987), makes use of both idiosyncratic and systematic covariates, which facilitates stress-testing. This approach has, to our knowledge, never been applied to credit risk before and we apply it to a mortgage loan portfolio of a major bank in South Africa.

This thesis aims to chart and explain the evolution of credit practices and the law’s reaction to them vis-à-vis the protection of borrowers between 1700 and 1974. The cat-and-mouse game played out between the credit industry and the legislature, and the longstanding tension between the credit needs of the commercial community and those of the small private borrower are of central importance. This thesis is primarily historical rather than theoretical; it seeks to describe and explain legal developments over time. But, in order to illuminate this development, the law will be viewed through the lens of a simple analytical framework based on the dichotomy between public law regulation, on the one hand, and the private law of contract, on the other. Viewed through this lens, it should be possible to position the law at any given stage of its development at a particular point on a scale of ‘regulatoriness’. The framework within which these rules were originally developed was, of course, neither intentionally nor self-consciously theoretical, but that is not to say that a theoretical framework lacks utility in legal historical inquiry.

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Digitized by Kansas Correctional Industries

Digitized by Kansas Correctional Industries

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 160-169). Available also in a digital version from Dissertation Abstracts.