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Simulation-based optimisation of the timing of loan recovery across different portfolios

机译:基于模拟的不同投资组合贷款恢复时间的优化

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A novel procedure is presented for the objective comparison and evaluation of a bank's decision rules in optimising the timing of loan recovery. This procedure is based on finding a delinquency threshold at which the financial loss of a loan portfolio (or segment therein) is minimised. Our procedure is an expert system that incorporates the time value of money, costs, and the fundamental trade-off between accumulating arrears versus forsaking future interest revenue. Moreover, the procedure can be used with different delinquency measures (other than payments in arrears), thereby allowing an indirect comparison of these measures. We demonstrate the system across a range of credit risk scenarios and portfolio compositions. The computational results show that threshold optima can exist across all reasonable values of both the payment probability (default risk) and the loss rate (loan collateral). In addition, the procedure reacts positively to portfolios afflicted by either systematic defaults (such as during an economic downturn) or episodic delinquency (i.e., cycles of curing and re-defaulting). In optimising a portfolio's recovery decision, our procedure can better inform the quantitative aspects of a bank's collection policy than relying on arbitrary discretion alone.
机译:提出了一种新的程序,用于客观比较和评估银行决策规则,以优化贷款恢复的时间。本程序是基于找到拖欠阈值的拖欠阈值,其中贷款投资组合的财务损失(或其中的段)最小化。我们的程序是一个专家系统,融入了金钱,成本和积累欠款与伪造未来利息收入之间的基本权衡之间的基本权衡。此外,该程序可用于不同的违法措施(除拖欠时的付款除外),从而允许间接比较这些措施。我们展示了一系列信用风险场景和投资组合组合的系统。计算结果表明,阈值最佳可以存在于支付概率(默认风险)和损失(贷款抵押品)的所有合理值中。此外,该程序对由系统违约(例如在经济衰退期间)或巨型违法期间(例如,固化和重新违约的周期)作出贡献的投资组合反应。在优化投资组合的恢复决定方面,我们的程序可以更好地通知银行收集政策的定量方面,而不是仅仅依赖任意自由裁量权。

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