Global ETD Search
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Showing 1 to 14 of 14 for “"Default prediction"”.
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Essays on Corporate Default Prediction
<p>Corporate bankruptcy prediction has received paramount interest in academic research, business practice and government regulation. The recent financial crisis, during which unexpected corporate insolvencies had caused severe damage to the aggregate economy, highlights the crucial importance of …
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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, containing …
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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 and …
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Three essays on corporate default prediction : special reference to corporate governance, default correlation and capital structure dynamics
… of three essays that investigate corporate defaults connected to corporate governance, default correlations and capital structure adjustment. Granting a loan requires mutual trust between lenders and borrower and depends on the flow of information. The relevance and the accuracy of the …
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Quantification of the default probability of the top 42 non-financial South African firms
… is to quantify the probability of firm default focusing on the top 42 non-financial firms listed on the Johannesburg Stock Exchange. This paper follows the same methodology as outlined in the Moody's KMV white papers in implementing the Merton (1974) model. The model of default …
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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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Modelling, forecasting and riding credit risk in the Sterling Eurobond market
… neural network model. Unlike the field of default prediction, little research has been done on forecasting the downgrade event. Filling this gap is of interest to banks and investors in periods of relative economic stability, in the context of value-at-risk models, and for the pricing of …
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Prediction of going-concern status: a probit model for the auditors
… No. 34 are inadequate and existing going-concern prediction models are flawed. In view of this, the objective of the dissertation is to construct a going-concern prediction model (hereafter called the Koh model) that is based upon improved statistical techniques and methodology. A sample of 165 …
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An AI-driven loan brokerage platform: integrating socio-economic factors, consumer financial behaviour, and multi-criteria decision analysis for responsible lending.
… in three interconnected phases: loan eligibility prediction, loan risk assessment, and suitable lender selection. The first phase of the research focuses on loan eligibility prediction, extending beyond conventional credit evaluation by incorporating five additional socio-economic factors: …