Date of this Version
Motivated by the growing practice of using social network data in credit scoring, we analyze the impact of using network-based measures on customer score accuracy and on tie formation among customers. We develop a series of models to compare the accuracy of customer scores obtained with and without network data. We also investigate how the accuracy of social network-based scores changes when consumers can strategically construct their social networks to attain higher scores. We find that those who are motivated to improve their scores may form fewer ties and focus more on similar partners. The impact of such endogenous tie formation on the accuracy of consumer score is ambiguous. Scores can become more accurate as a result of modifications in social networks, but this accuracy improvement may come with greater network fragmentation. The threat of social exclusion in such endogenously formed networks provides incentives to low-type members to exert effort that improves everyone's creditworthiness. We discuss implications for managers and public policy.
Originally published in Marketing Science © 2016 INFORMS
This is a pre-publication version. The final version is available at http://dx.doi.org/10.1287/mksc.2015.0949
social networks, credit score, customer scoring, social status, social discrimination, endogenous tie formation
Wei, Y., Yildirim, P., Van den Bulte, C., & Dellarocas, C. (2015). Credit Scoring with Social Network Data. Marketing Science, 35 (2), 234-258. http://dx.doi.org/10.1287/mksc.2015.0949
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Date Posted: 15 June 2018
This document has been peer reviewed.