New publication by SOCENT researcher Simon Cornée forthcoming in the Journal of Small Business Management and available on-line
“The Relevance of Soft Information for Predicting Small Business Credit Default: Evidence from a Social Bank”, by SOCENT researcher Simon Cornée, has been published as a CERMi-CEB working paper (WP 15-044) and is now available on-line. This article is also forthcoming in the Journal of Small Business Management.
Abstract: 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), the study highlights the relevance of including soft information (especially on management quality) to improve credit default prediction. Comparing the study’s 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.