摘要
建立了基于Elman神经网络的商业银行信贷风险识别及评估模型,并通过实例验证了模型的准确性和可靠性。研究过程及结果表明,基于Elman神经网络的商业银行信贷风险识别及评估模型能够很好地反映信贷过程中的非线性因素,准确地预测出完整的信贷风险评估指标和信用等级之间的映射关系,能快速评估和有效减低商业的信贷风险。一组实例结果显示该评估模型的准确率接近90%。
Credit-risk evaluation model for commercial bank loan based on Elman Neural Network is established. The example demonstrates the accuracy and reliability of the model. The research process and the results show that, commercial bank credit risk identification and assessment model based on Elman neural network can be well reflected in nonlinear credit factors during loan process, accurately predict a complete mapping relationship between the credit risk indicators and credit rating, quickly and effectively reduce the credit risk of the commercial. A special case shows that the accuracy of credit-risk evaluation model is nearly 90%.
出处
《科技和产业》
2008年第8期80-83,共4页
Science Technology and Industry
