In recent years, finance and corporate innovation has gained increasing attention and emerged as a significant subject of research from researchers and practitioners. Corporate credit rating is a complex and expensive process. However, most existing studies only use financial indicators to predict firm performance or credit ratings. The goal of this research is to examine the relationship between corporate innovation and a firm’s financial performance, as well as its credit rating structures by using financial and non-financial indicators. In this work, we propose a predictive model while utilizing machine learning classifiers to extract important features to predict corporate credit ratings. The preliminary experimental results show our proposed model can effectively predict the corporate credit rating by ensemble learning classifiers. Our research can help corporates identify the significant factors from financial and non-financial indicators to improve their credit ratings.
Kao, Yu-Chun; Tsou, Yu; Jhang, Pei-Yu; Chen, D N.; and Lai, Chia-Yu, "Credit Rating Prediction Using Corporate Innovation and Financial Ratios" (2020). PACIS 2020 Proceedings. 24.
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