DocumentCode :
695339
Title :
Can Sentiment Analysis Help Mimic Decision-Making Process of Loan Granting? A Novel Credit Risk Evaluation Approach Using GMKL Model
Author :
Dailing Zhang ; Wei Xu ; Yingqiu Zhu ; Xinwei Zhang
Author_Institution :
Sch. of Inf., Renmin Univ. of China, Beijing, China
fYear :
2015
fDate :
5-8 Jan. 2015
Firstpage :
949
Lastpage :
958
Abstract :
Credit risk assessment is a crucial process for financial institutions when granting commercial loans. However, the manual analysis of the overall condition of firms through customer due diligence reports is costly for both time and labor. This paper proposes a novel credit risk evaluation approach using GMKL model to automate the decision-making process. Sentiment indexes are generated by mining the opinions of the text content in customer due diligence reports and further used as input for model construction. The method distinguishes itself by innovatively employing sentiment analysis in credit risk assessment. A real-life loans granting dataset is utilized for verifying the performance of the method. The experiment results show that, when combining the traditional financial indicators along with the sentiment indexes, the classifiers trained by GMKL model can outperform several baseline models, successfully improving the accuracy of classification and also detecting the default loans.
Keywords :
credit transactions; data mining; decision making; financial management; learning (artificial intelligence); text analysis; GMKL model; baseline model; commercial loan; credit risk assessment; credit risk evaluation approach; customer due diligence report; decision-making process; default loan; financial indicator; financial institution; loan granting; opinion mining; real-life loans granting dataset; sentiment analysis; sentiment index; text content; Analytical models; Decision making; Dictionaries; Feature extraction; Indexes; Kernel; Sentiment analysis; GMKL model; credit risk evaluation; loan granting; sentiment analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences (HICSS), 2015 48th Hawaii International Conference on
Conference_Location :
Kauai, HI
ISSN :
1530-1605
Type :
conf
DOI :
10.1109/HICSS.2015.118
Filename :
7069922
Link To Document :
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