The Research Is Applying Financial And Non-financial Information To Establish A Pre-caution Model For Electronics Industry

One of commercial products for banking industry is the Credit Assessment. The overdue ratio of bank credit facilities is a key indication to measure the quality of Credit Assessment. In recent years, many of stock listed or OTC companies are often reported to dishonor the checks. This situation is deteriorating the Taiwan's banking Credit business that could also even be resulted into the survival issue of the involved bank. This research is aimed at analyzing and summarizing certain factors causing the overdue credit issue when the bank engaged such Credit Assessment business. By applying such methodology, the result may serve to be as a reference or guide for bank Credit Assessment business.In the past, the bank always review and analyze the Financial Statement so as to determine whether to grant the Credit facilities. However, this research applies not only the technical of Financial Analysis but also adding more variants of non-financial related information in an attempt to form a pre-caution model for warning enterprise. These following non-financial variants are included: 1) The change of Management or Finance responsible persons. 2) The change of Financial forecast. 3) The change from the opinion expressed by CPA. 4) The switch of CPAs.This research is based on the sampling from 26 previous stocks listed companies causing from financial difficulties plus 104 companies selecting from other 300 current stock listed companies. The total sampling population is extracted from these 300 companies. The main research method is applying the Logistic Regression model to identify the financial variants with significant so as to build up this pre-cautioned financial model. Furthermore, also adding those non-financial related variants to prove whether the forecast ability of this financial pre-caution model can be improved.As the result of substantial test: In this financial pre-caution model analysis, the debt ratio, net profit ratio and EPS are highly with significant. In those non-financial related variants, the change of management team, finance responsible person, the times of change CPA are also with high significant. Based on these statistics modeling by adding those non-financial variants, the forecast accuracy has been uplifted from 50% to 73% in this completed set of pre-cautioned financial model; for overall forecast even higher up to 93%.