Recognizing Financial Distress Patterns Using a Neural Network Tool
构建神经网络模型，通过识别财务数据模式来区分健康企业与困境企业，旨在为银行信贷员、投资者等金融从业者提供企业未来健康状况的早期预警信号。
This study builds neural networks (NNs) which estimate the future financial health of firms. A neural network is a relatively new mathematical approach for recognizing discriminating patterns in data. We use NNs here to identify financial data patterns which consistently distinguish generally healthy firms from distressed ones. The purpose is to detect early warning signals of distressful conditions in currently viable firms. Being able to form highly reliable early forecasts of the future health of firms is critical to bank lending officers, investors, market analysts, portfolio managers, insurers, and many others in the field of finance.