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This article proposes a method for measuring the latent risks involved in therecovery process of non performing loans in financial institutions and businessfirms that deal with collection and recovery processes. To that end, we applythe competing risks model referred to in the literature as the promotion timemodel. The result achieved is the probability of credit recovery for aportfolio segmented into groups based on the information available. Within thecontext of competing risks, application of the technique yielded an estimationof the number of latent events that concur to the credit recovery event. Withthese results in hand, we were able to compare groups of defaulters in terms ofrisk or susceptibility to the recovery event during the collection process, andthereby determine where collection actions are most efficient. We specify thePoisson distribution for the number of latent causes leading to recovery, andthe Weibull distribution for the time up to recovery. To estimate the modelparameters, we use the maximum likelihood method. Finally, the model wasapplied to a sample of defaulted loans from a financial institution.

Recovery Risk: Application of the Latent Competing Risks Model to Non performing Loans