Typescript (photocopy). / Digitized by Kansas Correctional Industries

Memoria (licenciado en ciencias jurídicas y sociales) / El presente trabajo, describiendo y considerando la situación en que se encuentran las pequeñas y microempresas en nuestro país, analiza sus escenarios en relación al crédito bancario formal. Destacando que los problemas se dan en materia de acceso, monto y plazos. Al mismo tiempo, diferencia los conceptos de crédito a la microempresa y microcrédito, atendiendo al origen de este último, para que el tema no se preste a confusión al momento de abordar una posible solución para hacer frente a los elevados costos de transacción y al riesgo crediticio del cual son presa, no sólo la microempresas, sino también las pequeñas, en el marco del crédito bancario tradicional. Por último, se plantea al Credit Scoring, sistema de evaluación estadístico cuantitativo y luego de analizarlo pormenorizadamente, como una de las mediadas a adoptar por parte de los privados – la banca formal – con el objeto superar la brecha que genera la falta de historial crediticio en este sector empresarial.

Diplomová práce se zabývá přínosy a dopady nové směrnice pro výpočet kapitálového požadavku Basel II do procesů českých bank. Práce popisuje jednotlivé přístupy k měření kreditního, operačního a stručně i tržního rizika. Stěžejní část diplomové práce tvoří metodický popis vývoje scoringového modelu, splňující požadavky Basel II, pro výpočet pravděpodobnosti defaultu a jeho samotná konstrukce nad reálnými daty poskytnutými společností ČSOB Leasing a.s. Praktické využití diplomové práce je v oblasti řízení rizika a v procesu schvalování zákaznických smluv v leasingových společnostech.

For my senior thesis, I am planning to blend my mathematical studies with my second field of study, psychology. In particular, to develop and test various scoring methods for a multidimensional, psychometric measure of social skills/competence. I would work with the Social Skills Inventory (see below) and an existing data set, using statistical modelling to design a more representative total score measure. The current total score measure does not appear to take into account balances and value weights of the six inventory items.

This thesis investigates the use of newly-developed survival analysis tools for credit scoring. Credit scoring techniques are currently used by financial institutions to estimate the probability of a customer defaulting on a loan by a predetermined time in the future. While a number of classification techniques are currently used, banks are now becoming more concerned with estimating the lifetime of the loan rather than just the probability of default. Difficulties arise when using standard statistical techniques due to the presence of censoring in the data. Survival analysis, originating from medical and engineering fields, is an area of statistics that typically deals with censored lifetime data. The theoretical developments in this thesis revolve around linear regression for censored data, in particular the Buckley-James method. The Buckley-James method is analogous to linear regression and gives estimates of the mean expected lifetime given a set of explanato ry variables. The first development is a measure of fit for censored regression, similar to the classical r-squared of linear regression. Next, the variable-reduction technique of stepwise selection is extended to the Buckley-James method. For the last development, the Buckley-James algorithm is altered to incorporate non-linear regression methods such as neural networks and Multivariate Adaptive Regression Splines (MARS). MARS shows promise in terms of predictive power and interpretability in both simulation and empirical studies. The practical section of the thesis involves using the new techniques to predict the time to default and time to repayment of unsecured personal loans from a database obtained from a major Australian bank. The analyses are unique, being the first published work on applying Buckley-James and related methods to a large-scale financial database.

The main purpose of this study was to explore the influence of using "scientific inquiry ability scoring rubric" to be the learning scaffold and self-assessment stratagem in experiment curriculum on students' scientific inquiry ability. A quasi-experimental study was implemented in a university for one semester. Of the two classes participated in this study, one received the designed teaching stratagem and the other the traditional experiment curriculum. Students' reports were scored and sufficient data of quality were collected after each experiment to test the differences of the two classess, further analysed the self-assessment data and learning-questionnaire to assess students¡¦ perceptions. In addition, the influence of students' motive on learning was also investigated. The results obtained from this study are summarized as follows: 1. Among six abilities studied those belonging to "Nature of scientific inquiry" and "Communication"¡]¡¨forming a question¡¨, ¡¨the completeness of procedures¡¨, ¡¨the sufficiency of data¡¨, ¡§the organization of data¡¨, ¡§transferring data¡¨, ¡§reviewing and evaluating¡¨¡^had a greater progress under this stratagem. 2. Students changed step by step on four inquiry-ability dimensions (i.e., bring up self inquiry questions, try to transfer data to improve science communication etc.) during this investigation period. 3. The correlation between assessments of teachers' and those of students' increased gradually, but there was no significant difference in performance between hit and miss self-assessors. 4. Students had positive attitudes toward the self-assessment questionnaire. About 80¢Mstudents accepted that using the rubrics was beneficial for learning."Attitude" and "Science Learning Value" are the two items of students' motive that showed significant relation with their learning effects.

Thesis (M. Sc.)--University of Hong Kong, 2002. / Includes bibliographical references.

Most lending institutions are aware of the importance of having a well-performing credit scoring model or scorecard and know that, in order to remain competitive in the credit industry, it is necessary to continuously improve their scorecards. This is because better scorecards result in substantial monetary savings that can be stated in terms of millions of dollars. Thus, there has been increasing interest in the application of new classifiers in credit scoring from both practitioners and researchers in the last few decades. Most of the recent work in this field has focused on the use of new and innovative techniques to classify applicants as either 'credit-worthy' or 'non-credit-worthy', with the aim of improving scorecard performance. In this thesis, we investigate the suitability of intelligent systems techniques for credit scoring. In particular, intelligent systems that use immunological metaphors are examined and used to build a learning and evolutionary classification algorithm. Our model, named Simple Artificial Immune System (SAIS), is based on the concepts of the natural immune system. The model uses applicants' credit details to classify them as either 'credit-worthy' or 'non-credit-worthy'. As part of the model development, we also investigate several techniques for selecting variables from the applicants' credit details. Variable selection is important as choosing the best set of variables can have a significant effect on the performance of scorecards. Interestingly, our results demonstrate that the traditional stepwise regression variable selection technique seems to perform better than many of the more recent techniques. A further contribution offered by this thesis is a detailed description of the scorecard development process. A detailed explanation of this process is not readily available in the literature and our description of the process is based on our own experiences and discussions with industry credit risk practitioners. We evaluate our model using both publicly available datasets as well as a very large set of real-world consumer credit scoring data obtained from a leading Australian bank. The evaluation results reveal that SAIS is a competitive classifier and is appropriate for developing scorecards which require a class decision as an outcome. Another conclusion reached is one confirmed by the existing literature, that even though more sophisticated scorecard development techniques, including SAIS, perform well compared to the traditional statistical methods, their performances are not statistically significantly different from the statistical methods. As with other intelligent systems techniques, SAIS is not explicitly designed to develop practical scorecards which require the generation of a score that represents the degree of confidence that an applicant will belong to a particular group. However, it is comparable to other intelligent systems techniques which are outperformed by statistical techniques for generating p ractical scorecards. Our final remark on this research is that even though SAIS does not seem to be quite suitable for developing practical scorecards, we still believe that there is room for improvement and that the natural immune system of the body has a number of avenues yet to be explored which could assist with the development of practical scorecards.

Mannheim, Univ., Diss., 2002.

No description available.