I explore whether big-data sources can crowd out the value of private information acquired through lending relationships. Institutional lenders have been shown to exploit their access to borrowers' private information by trading on it in financial markets. As a shock to this advantage, I use the release of the satellite data of car counts in store parking lots of U.S. retailers. This data provides accurate and near–real-time signals of firm performance, which can undermine the value of borrowers' private information obtained through syndicate participation. I find that once the satellite data becomes commercially available, institutional lenders are less likely to participate in syndicated loans. The effect is more pronounced when borrowers are opaque or disseminate private information to their lenders earlier and when the data predicts borrower performance more accurately. I also show that institutional lenders’ reduced demand for private information leads to less favorable loan terms for borrowers.

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大数据已然消失：机构贷款人对私人信息的需求

我探讨大数据源是否可以挤出通过借贷关系获取的私人信息的价值。事实证明，机构贷款人通过在金融市场上进行交易来利用其获取借款人私人信息的机会。作为对这一优势的震惊，我使用了美国零售商商店停车场汽车数量的卫星数据的发布。这些数据提供了准确且近乎实时的公司业绩信号，这可能会削弱借款人通过参与银团获得的私人信息的价值。我发现，一旦卫星数据商业化，机构贷款人就不太可能参与银团贷款。当借款人不透明或较早向贷款人传播私人信息以及数据更准确地预测借款人的表现时，这种影响会更加明显。我还表明，机构贷款人对私人信息的需求减少导致对借款人的贷款条件不利。