Research on the Factors and Prediction Models of Personal Credit Business Income

• Main Authors: TSAI, SHEN-CHUN, 蔡紳濬
• Other Authors: Hou,Chia-Ding
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/43r86s

碩士 === 輔仁大學 === 統計資訊學系應用統計碩士在職專班 === 106 === In 2008, the subprime mortgage storm caused a global financial tsunami. As a result, the credit default rate of various countries increased, which accelerated the credit crunch of the entire financial market. Taiwan could not stay out of the way. However, after the storm losses in previous years, Banks is recognized that the overall economic good and the bank's profit and loss are closely related and integrated. Therefore, how to predict the profit and loss of personal credit business income through the overall economic factors has become a topic that banks have to think about. This study attempts to predict the changes in the income of the personal credit business through the main overall economic factors. In the analysis, the sources of income of the personal credit business are divided into important income targets such as the total number of personal credits per month, the total monthly amount and the monthly average interest rate. Using Pearson correlation analysis, variance inflation factor and stepwise regression model, the three major income forecasting models of personal credit business were built. The results showed that in addition to the overall economic variables, the total number of individuals who joined personal credits per month, total monthly When the amount is forecasted together with important income variables such as the monthly average interest rate, the model has the best effect, and the R2 can reach 0.888, 0.895 and 0.862, respectively, which can provide a reference for future changes in the income of the personal credit business.