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Open AccessJournal ArticleDOI

Time to default in credit scoring using survival analysis: a benchmark study

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TLDR
It is found that spline-based methods and the single event mixture cure model perform well in the credit risk context.
Abstract
We investigate the performance of various survival analysis techniques applied to ten actual credit data sets from Belgian and UK financial institutions. In the comparison we consider classical survival analysis techniques, namely the accelerated failure time models and Cox proportional hazards regression models, as well as Cox proportional hazards regression models with splines in the hazard function. Mixture cure models for single and multiple events were more recently introduced in the credit risk context. The performance of these models is evaluated using both a statistical evaluation and an economic approach through the use of annuity theory. It is found that spline-based methods and the single event mixture cure model perform well in the credit risk context.

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Deep Neural Networks for Survival Analysis Based on a Multi-Task Framework.

TL;DR: A new method to calculate survival functions using the Multi-Task Logistic Regression model as its base and a deep learning architecture as its core, which outperforms the MTLR in all the experiments disclosed in this paper.
Journal ArticleDOI

A Novel behavioral scoring model for estimating probability of default over time in peer-to-peer lending

TL;DR: The results of an empirical analysis show that the proposed ensemble mixture random forest (EMRF) has a better performance in terms of predicting the monthly dynamic probability of default, while compared with standard mixture cure model, Cox proportional hazards model and logistic regression.
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Computational approaches and data analytics in financial services: A literature review

TL;DR: An overview of the main financial applications of computational and data analytics approaches, focusing on the coverage of the recent developments and trends is provided.
References
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Book ChapterDOI

Regression Models and Life-Tables

TL;DR: The analysis of censored failure times is considered in this paper, where the hazard function is taken to be a function of the explanatory variables and unknown regression coefficients multiplied by an arbitrary and unknown function of time.
Book

Analysis of Survival Data

David Cox, +1 more
TL;DR: In this article, the authors give a concise account of the analysis of survival data, focusing on new theory on the relationship between survival factors and identified explanatory variables and conclude with bibliographic notes and further results that can be used for student exercises.
Book

Modeling Survival Data: Extending the Cox Model

TL;DR: A Cox Model-based approach was used to estimate the Survival and Hazard Functions and the results confirmed the need for further investigation into the role of natural disasters in shaping survival rates.
Journal ArticleDOI

The statistical analysis of failure time data

TL;DR: In this article, the authors proposed a regression model for failure time distributions in the context of counting process models and showed that the model can be used to estimate the probability of failure.
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