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Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/77427


Title: Soft Information and Small Business Lending
Authors: Chen, Yehning;Huang, Rachel J.;Tsai, John;Tzeng, Larry Y.
黃瑞卿;曾郁仁
Contributors: 風險與保險研究中心
Keywords: Soft information;Small business lending;Default prediction;Credit scoring;G21;G33
Date: 2015-02
Issue Date: 2015-08-05 14:37:22 (UTC+8)
Abstract: Using data from a Taiwanese finance company, this paper empirically investigates the value of soft information, information that requires the subjective interpretation by the loan officers who collect it and cannot be credibly transmitted to others, for making small business loans. It finds that the use of soft information significantly improves the power of default prediction models. It also identifies the types of soft information that are helpful for predicting loan defaults. In addition, it shows that borrowers with more favorable soft information enjoy lower interest rates. These results imply that soft information is important for small business lending.
Relation: Journal of Financial Services Research,47,(1),115-133
Data Type: article
DOI link: http://dx.doi.org/10.1007/s10693-013-0187-x
Appears in Collections:[Department of Risk Management and Insurance] Periodical Articles

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