Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 32 for “"Loan default"”.
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Industrial loan default: the case of Bangladesh
… distress since the early 1970s due to persistent loan defaults. Despite the application of a number of remedial measures, industrial loan default problems continued to haunt the IDFIs. The massive loan loss has not only impaired the viability of many financial institutions, but also made them …
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Leveraging Machine Learning and Causal Inference for Loan Default Prediction
… combined with causal inference to predict loan defaults in peer-to-peer lending. Accurately forecasting loan defaults is crucial for mitigating financial risk and optimizing lending strategies. This analysis is based on multiple datasets of loan applications spanning over a decade, …
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The probability of Chinese mortgage loan default and credit scoring
… widely used in business lending because business loan differ substantially across household borrowers, making it more difficult to build up an accurate scoring method. However, this has changed. The complexity and flexibility of statistical models and advanced computing technology have made such …
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Identification of relevant predictors of loan default using the Elastic Net model
The timely prediction of loan default plays an important role in lending decisions and monitoring loans. However, there has been little development of models for the selection of relevant variables for the prediction of loan default. This study identifies financial and economic indicators for the …
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An exploration of alternative features in micro-finance loan default prediction models
… can be used to improve the performance of loan default prediction models. The improvement gained by using alternative features is measured by comparing loan default prediction models trained using only traditional credit scoring data to models developed using a combination of traditional …
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Why Risk It? The Effect of Risk and Time Preferences on Microfinance Loan Default
… about the characteristics of those who</p> <p>default on their loans. Understanding the behavior of borrowers is an important</p> <p>component of mitigating adverse selection and the moral hazard of lending. Both</p> <p>of these concepts embody some of the greatest challenges faced by …
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An investigation into the causes of customer loan default at the Agricultural Bank of Namibia, Oshakati branch
… has faced credit risk of borrowers not repaying loans on time as per the loan contract. This has resulted in financial losses to the ban . The Bank is concerned with the low rate of loan recovery on its scheduled loan instalments. This concem is due to clients defaulting, resulting in a …
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Agency risk in CMBS default resolution : a case study of the Peter Cooper Village - Stuyvesant Town mortgage loan default
… approximately $410 billion of maturing CMBS loans are expected not to able to refinance; that is, they are in high risk of default. The current real estate downturn has not only pushed delinquencies to a historic high but has also inflicted losses to bondholders. When losses are realized …
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Potential Effects of Modifying the Masagana 99 Program of the Philippines
… threatened by the poor repayment of production loans by farmer-borrowers. Loan default rate is high (about 24%) in spite of the claimed increases in farm productivity and income, and farmers' access to cheap loans in the program.
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A Comparative Analysis of Loan Repayments between Credit Cooperatives Societies and Microfinance Institutions Borrowers in Babati District
… the main objective of comparing the extent of loan repayment between MFIs and SACCOS, and to identify the causes of poor loan repayments. Hence suggest solutions for improving borrower’s livelihood. The specific objectives of the study were to evaluate the percentage of loan default and factors …
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What Text Information Helps to Reduce Default Risk
… investigates the predictive factors influencing loan default in the context of peer-to-peer (P2P) lending, with a particular focus on the integration of voluntarily provided text data alongside traditional financial, demographic, and loan information. Using a dataset of over 296,000 borrowers …
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Improved Peer-to-Peer Lending Credit Scoring Mechanism using Machine Learning Techniques
… creditworthiness is important because many P2P loans are not secured by collateral. Banks use credit scoring to evaluate borrower’s creditworthiness and reduce potential loan default risk. However, in P2P lending platform effective credit scoring models are hard to build due to insufficient …
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Analysis of distressed Commercial Mortgage backed Securities (CMBS) loans and special servicing : a case study
… exposed real estate properties to high risk of default, pushing the CMBS loans delinquency rate to 10.32% in June 2020. As such an economic halt is likely to prevail, it is expected that the Commercial Real Estate (CRE) market would experience more distress in terms of debt service. Thus, it is …
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Machine Learning for Credit Default Risk
… used to enhance traditional approaches to credit default forecasting and pricing. In the first essay, we provide empirical evidence in favour of a widespread non-linear, time-varying relationship between sovereign credit risk and macroeconomic fundamentals across OECD countries. Random forests …
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Three Essays in Applied Microeconomics
… first chapter, I measure the impact of student loan debt on young, college-educated workers' decisions regarding labor supply and enrollment in graduate school. I exploit variation in student loan debt driven by the formulas that determine Federal Student Aid in order to identify these effects. …
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