Essays about: "Default-probability"
Showing result 1 - 5 of 23 essays containing the word Default-probability.
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1. Portfolio Risk Modelling in Venture Debt
University essay from KTH/Matematisk statistikAbstract : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. READ MORE
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2. Peeking Through the Leaves : Improving Default Estimation with Machine Learning : A transparent approach using tree-based models
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : In recent years the development and implementation of AI and machine learning models has increased dramatically. The availability of quality data paving the way for sophisticated AI models. Financial institutions uses many models in their daily operations. READ MORE
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3. Artificial Neural Networks and Inductive Biases for Multi-Instance Multi-Modal Tabular Data : A Case Study for Default Probability Estimation in Small-to-Medium Enterprise Lending
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The success of artificial neural networks in homogeneous data domains such as images, textual data, and audio and other signals has had considerable impact on Machine Learning and science in general. The domain of heterogeneous tabular data, while arguably much more common, remains much less explored with regards to artificial neural networks and deep learning. READ MORE
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4. Deep Learning Approach for Time- to-Event Modeling of Credit Risk
University essay from KTH/Matematisk statistikAbstract : This thesis explores how survival analysis models performs for default risk prediction of small-to-medium sized enterprises (SME) and investigates when survival analysis models are preferable to use. This is examined by comparing the performance of three deep learning models in a survival analysis setting, a traditional survival analysis model Cox Proportional Hazards, and a traditional credit risk model logistic regression. READ MORE
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5. Prediction of Short-term Default Probability of Credit Card Invoices Using Behavioural Data
University essay from KTH/Matematisk statistikAbstract : Probability of Default (PD) is a standard metric to model and monitor credit risk, a major risk facing financial institutions. Traditional PD models are used to forecast risk levels in the long-term, while short-term PD predictions are rarer, but they can support management decisions on an operational level. READ MORE
