English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

A theoretical method is empirically illustrated in finding the best time toforsake a loan such that the overall credit loss is minimised. This ispredicated by forecasting the future cash flows of a loan portfolio up to thecontractual term, as a remedy to the inherent right-censoring of real-world`incomplete' portfolios. Two techniques, a simple probabilistic model as wellas an eight-state Markov chain, are used to forecast these cash flowsindependently. We train both techniques from different segments withinresidential mortgage data, provided by a large South African bank, as part of acomparative experimental framework. As a result, the recovery decision'simplied timing is empirically illustrated as a multi-period optimisationproblem across uncertain cash flows and competing costs. Using a delinquencymeasure as a central criterion, our procedure helps to find a loss-optimalthreshold at which loan recovery should ideally occur for a given portfolio.Furthermore, both the portfolio's historical risk profile and forecastingthereof are shown to influence the timing of the recovery decision. This workcan therefore facilitate the revision of relevant bank policies or strategiestowards optimising the loan collections process, especially that of securedlending.

The loss optimisation of loan recovery decision times using forecast cash flows