In order to stress test loan portfolios for the impacts of climate change, historical events need to be analyzed to create templates to stress test for future events. Using the 2012 Midwestern US drought as an example, this work creates a stress-testing template for future droughts. The analysis...

The credit risk measure, Expected Loss (EL) is defined as the product of the three risk parameters: probability of default (PD), loss given default (LGD) and exposure at default (EAD). EL is central to risk management, profit estimation, calculating regulatory capital requirements and the...

Based on a rich data set of recoveries donated by a debt collection business, recovery rates fornon-performing loans taken from a single European country are modelled using linear regression,linear regression with Lasso, beta regression and inflated beta regression. We also propose atwo-stage...

Based on a rich dataset of recoveries donated by a debt collection business, recovery rates for non-performing loans taken from a single European country are modelled using linear regression, linear regression with Lasso, beta regression and inflated beta regression. We also propose a two-stage...

We compare the performances of a wide set of regression techniques and machine learning algorithms for predicting recovery rates on non-performing loans, using a private database from a European debt collection agency. We find that rule-based algorithms such as Cubist, boosted trees and random...

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions...