Some Methods for Estimating Financial Risks in Banking

N. Kuznietsova, M. Seebauer, S. Zabielin
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引用次数: 2

Abstract

This paper is devoted to the investigation of the possibilities of using neural networks, Altman model and linear regression for Z-score and Beta index prediction. These methods could be used for evaluating the probability of bankruptcy for companies-borrowers, individuals, portfolio of credits and the bank in whole. In this work Z-score was predicted for Bank of America based on Altman model and the best model for its forecasting was neural network backpropagation with the configuration (2,3,3,3,3,3,3,3,3,2). In future research is planning to make the further investigation of the possibilities to use the other data mining methods for evaluating the probability of risk and forecasting of expected losses after its appearance.
银行业财务风险评估的几种方法
本文探讨了利用神经网络、Altman模型和线性回归进行Z-score和Beta指数预测的可能性。这些方法可用于评估公司-借款人,个人,信贷组合和整个银行的破产概率。本文基于Altman模型对美国银行进行Z-score预测,其预测的最佳模型是配置为(2,3,3,3,3,3,3,3,2,2)的神经网络反向传播模型。在未来的研究中,计划进一步研究使用其他数据挖掘方法来评估风险概率和预测风险出现后的预期损失的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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