Abstract:
A theoretical method is empirically illustrated in finding the best time to forsake a loan such that the overall credit
loss is minimised. This is predicated by forecasting the future cash flows of a loan portfolio up to the contractual
term, as a remedy to the inherent right-censoring of real-world ‘incomplete’ portfolios. Two techniques, a simple
probabilistic model as well as an eight-state Markov chain, are used to forecast these cash flows independently. We
train both techniques from different segments within residential mortgage data, provided by a large South African
bank, as part of a comparative experimental framework. As a result, the recovery decision’s implied timing is
empirically illustrated as a multi-period optimisation problem across uncertain cash flows and competing costs.
Using a delinquency measure as a central criterion, our procedure helps to find a loss-optimal threshold at which
loan recovery should ideally occur for a given portfolio. Furthermore, both the portfolio’s historical risk profile and
forecasting thereof are shown to influence the timing of the recovery decision. This work can therefore facilitate the
revision of relevant bank policies or strategies towards optimising the loan collections process, especially that of
secured lending.
