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...