Modeling Repayment Behavior of Consumer Loan in Portfolio across Business Cycle: A Triplet Markov Model Approach

Abstract

With a view to develop a more realistic model for credit risk analysis in consumer loan, our paper addresses the problem of how to incorporate business cycles into a repayment behavior model of consumer loan in portfolio. A particular Triplet Markov Model (TMM) is presented and introduced to describe the dynamic repayment behavior of consumers. The particular TMM can simultaneously capture the phases of business cycles, transition of systematic credit risk of a loan portfolio, and Markov repayment behavior of consumers. The corresponding Markov chain Monte Carlo algorithms of the particular TMM are also developed for estimating the model parameters. We show how the transition of consumers’ repayment states and systematic credit risk of a loan portfolio are affected by the phases of business cycles through simulations.

Deep parameterizations of pairwise and triplet Markov models for unsupervised classification of sequential data

“…over discrete auxiliary latent r.v. ; the latter being the only option that has been considered in the literature so far [Gorynin et al, 2018, Li et al, 2019, Chen and Jiang, 2020. These experiments show the interesting capabilities of the generalized models to provide results in presence of very general noises.…”

“…Finally, we consider a discrete version of the MTMC (di-MTMC) in which ∈ { 1 , 2 } is discrete [Gorynin et al, 2018, Li et al, 2019, Chen and Jiang, 2020. For this model, Alg.…”

Non-stationary data segmentation with hidden evidential semi-Markov chains

“…However, when each 𝑈 𝑛 take its values in a finite set, MPM is still computable in a similar way it is done in HMCs and PMCs. TMCs have been successively used in image segmentation [24], [25], [26], normalized difference vegetation index modelling [27], activity classification [28], repayment of consumer loan modelling [29], non-stationary fuzzy data segmentation [30], [31], or still respiratory signal analysis [32]. As 𝑈 𝑁 is arbitrary in the general case, it may not have a practical interpretation.…”