پیش بینی ورشکستگی برای SMEs با استفاده از داده های ارتباطی Bankruptcy prediction for SMEs using relational data
- نوع فایل : کتاب
- زبان : انگلیسی
- ناشر : Elsevier
- چاپ و سال / کشور: 2018
توضیحات
رشته های مرتبط مهندسی صنایع
گرایش های مرتبط برنامه ریزی و تحلیل سیستم ها
مجله سیستم های پشتیبانی تصمیم گیری – Decision Support Systems
دانشگاه Department of Engineering Management – University of Antwerp – Belgium
منتشر شده در نشریه الزویر
کلمات کلیدی داده کاوی، داده های مرتبط، تجزیه و تحلیل شبکه، پیش بینی ورشکستگی، SME
گرایش های مرتبط برنامه ریزی و تحلیل سیستم ها
مجله سیستم های پشتیبانی تصمیم گیری – Decision Support Systems
دانشگاه Department of Engineering Management – University of Antwerp – Belgium
منتشر شده در نشریه الزویر
کلمات کلیدی داده کاوی، داده های مرتبط، تجزیه و تحلیل شبکه، پیش بینی ورشکستگی، SME
Description
1. Introduction Bankruptcy prediction is a widely studied topic due to its importance for the banking sector. The current volume of outstanding debt to non-financial firms in Belgium is about 122 billion euros, which is 123% of GDP as measured in the first quarter of 2015 [26]. The size of corporate lending makes sound lending decisions a matter of national interest. To counter the adverse effects of these high exposures, Basel II and III have introduced capital requirements that are more sensitive to risk. For many SMEs this implies that banks are charging a higher risk premium [5]. Investing in improved bankruptcy prediction models is therefore in the interest of both the banks and the clients, as better predictions will reduce risk and lower the subsequent risk premia. Research on bankruptcy prediction has largely focused on traditional data such as financial ratios, stock data or macroeconomic data [10, 34]. However, it is often noted that the (in)competence of the managerial team has a great influence on a company’s chance of survival [29]. To measure a business manager’s or board member’s competence, one could take a look at the business history of this person.
