The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank
利用法国一家社会银行的389笔小企业贷款数据，研究发现软信息（尤其是管理质量）能显著提升信用违约预测效果，且借款人信息越不透明，软信息预测价值越高。
Using a unique, hand-collected database of 389 small loans granted by a French social bank dealing with genuinely small, informationally opaque businesses (mainly social enterprises), our study highlights the relevance of including soft information (especially on management quality) to improve credit default prediction. Comparing our findings with those of previous studies also reveals that the more opaque the borrower, the higher the predictive value of soft information in comparison with hard. Finally, a cost-benefit analysis shows that including soft information is economically valuable once collection costs have been accounted for, albeit to a moderate extent.