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Modeling hard and soft facts for SMEs: Some international evidence
Journal of International Financial Management & Accounting ( IF 2.808 ) Pub Date : 2019-07-08 , DOI: 10.1111/jifm.12108
Massimo Matthias 1 , Michele Giammarino 1 , Giampaolo Gabbi 1, 2
Affiliation  

This paper asks how well the use of quantitative and qualitative variables can improve the assessment of companies' creditworthiness and how this result can be influenced by the economic and financial peculiarities of countries. We harden qualitative variable measures to model soft information aimed at scoring microfirms, small, and medium‐sized firms. The structural survey covers Germany, Italy, and the UK in a sample of about 17 thousand companies observed during the financial crisis. Soft facts are determined within the balanced scorecard framework in order to find out the impact of customers, business processes, learning and growth, and financial perspectives. Our findings show that credit models integrating soft variables optimize the risk estimation, but estimates are country‐specific and should be tailored to the characteristics of each economic system.

中文翻译:

中小企业的硬性和软性事实建模:一些国际证据

本文提出了定量和定性变量的使用如何改善对公司信誉度的评估,以及该结果如何受到国家经济和金融特点的影响。我们强化定性变量测度以对软信息建模,以对微型公司,中小型公司进行评分。结构性调查涵盖了金融危机期间观察到的大约17,000家公司的样本中的德国,意大利和英国。在平衡记分卡框架内确定事实,以便找出客户,业务流程,学习和增长以及财务角度的影响。我们的发现表明,结合了软变量的信用模型可以优化风险估算,
更新日期:2019-07-08
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