دانلود مقاله مطالعه اثر اطلاعات مصرف کننده بر ارزیابی ریسک اعتباری شخصی
چکیده
مقدمه
تحقیقات پیشین
داده ها و توضیحات متغیر
مدل ارزیابی و نتایج تجربی
بحث
نتیجه گیری
منابع
Abstract
Introduction
Previous Research
Data and Variable Description
Evaluation Model and Empirical Results
Discussion
Conclusions
References
چکیده
این مطالعه اطلاعات وام گیرندگان چینی را از پلتفرمی انتخاب می‌کند که هم خرید آنلاین و هم خدمات وام مصرف‌کننده را به عنوان نمونه دارد، تأثیر اطلاعات مصرف‌کننده را در ارزیابی ریسک اعتباری شخصی مورد مطالعه قرار می‌دهد و از مدل رگرسیون لجستیک، الگوریتم ماشین تقویت گرادیان نور (LightGBM) و توضیح افزودنی Shapley (SHAP) استفاده می‌کند. نتایج نشان می‌دهد که اطلاعات تمام گروه‌های وام مصرف‌کننده را نمی‌توان تحت پوشش اطلاعات اعتباری سنتی قرار داد. اطلاعات مصرف کننده می تواند به پیش بینی رفتار بازپرداخت وام گیرنده کمک کند و از ارزیابی ریسک اعتباری شخصی موثر پشتیبانی کند. افزودن اطلاعات مصرف به مدل ارزیابی ریسک اعتباری شخصی می تواند دقت مدل را به طور موثر بهبود بخشد. متغیرهای مدل e بر اساس اهمیت ویژگی رتبه‌بندی می‌شوند و 5 شاخص مصرف در 5 شاخص اول اهمیت ویژگی وجود دارد که ارزش و تأثیر اطلاعات مصرف را در ارزیابی ریسک اعتباری شخصی تأیید می‌کند. این مطالعه نه تنها تأثیر و ارزش اطلاعات مصرف کننده را در ارزیابی ریسک اعتباری شخصی به طور مؤثر آشکار می کند، بلکه ایده های جدیدی را برای توسعه بازار مالی مصرف کننده ارائه می دهد.
توجه! این متن ترجمه ماشینی بوده و توسط مترجمین ای ترجمه، ترجمه نشده است.
Abstract
This study selects Chinese borrowers’ information from a platform that has both online shopping and consumer loan service as sample, studies the effect of consumer information in personal credit risk evaluation, and uses the lLogistic regression model, light gradient boosting machine (LightGBM) algorithm, and Shapley Additive Explanation (SHAP). The results show that the information of all consumer loan groups cannot be covered by traditional credit information. Consumer information can help predict the behavior of borrower’s repayment and provide support for personal credit risk evaluation effective. Adding consumption information to the personal credit risk evaluation model can improve the accuracy of the model effectively. The model variables are ranked by feature importance, and there are 5 consumption indicators in the first 5 indicators of feature importance, which further verifies the value and effect of consumption information in personal credit risk evaluation. This study not only reveals the effect and value of consumer information in personal credit risk evaluation effectively, but also provides new ideas for the development of consumer financial market.
Introduction
At present, a new round of global scientific and technological revolution continues to deepen, financial technology is rising rapidly, and new business forms, new models, and new products emerge one after another. It not only changes the operation mode of traditional financial services, but also promotes the development of Internet personal consumption loans. At the same time, the vigorous development of personal consumer loans will have an impact on customers’ intertemporal consumption behavior. Under this background, the personal credit risk evaluation index system is becoming more and more abundant, and multi-dimensional and massive data are fused and processed. Big data credit investigation is an inevitable trend of personal credit risk evaluation. Nevertheless, some data are missing and the amount of data is lacking, so it is difficult to train [1]. The PBC credit investigation system cannot cover all borrowers’ information, which requires financial institutions to explore indicators beyond traditional personal credit risk evaluation index system. The traditional evaluation index system rarely uses consumption information as the evaluation index of personal credit risk. Can consumer information be used for personal credit risk assessment? What is the value and function of consumer information in personal credit risk evaluation? This is the question to be answered in this paper. This study uses the Chinese borrower’s data of a platform that has both online shopping and consumer loan to explore this problem.
Conclusions
Through the empirical analysis of personal credit risk evaluation, this paper describes the characteristics and influencing factors of consumption information and proves the value and effect of consumption information in personal credit risk evaluation. In order to alleviate the long-term credit constraints, it is necessary to promote the development of the credit market on the premise of meeting the loan needs of tail customers. With the strong promotion of financial technology, Internet credit products came into being. However, the current credit investigation system cannot cover all the information of loan demanders, and the credit risk evaluation results are inaccurate. Therefore, how to evaluate credit risk effectively has become an urgent problem to be solved. This requires financial institutions to seek information that can widely cover all loan demanders objectively. Different from the traditional credit information, consumer information has the characteristics of easy access and prominent preference, which can be used as an effective supplement to the traditional credit information. Evaluation of the effect of consumer information effective has become the focus of attention in personal credit risk evaluation.