Gone with the Big Data: Institutional Lender Demand for Private Information

I explore whether the value of borrowers’ private information is an important determinant of institutional lender participation in syndicated loans. Institutional lenders have been shown to exploit their access to borrowers’ private information by trading on it in financial markets. As a shock to these lenders’ private information advantage, I utilize the release of the satellite image data of car counts in store parking lots of U.S. retail firms. The satellite data provides accurate and near-real-time signals of firm performance, which undermines 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. Consistent with institutional lenders’ information-demand channel, the effect of the satellite data coverage is more pronounced when borrowers are opaque or disseminate private information to their lenders earlier. The satellite data coverage further attenuates institutional lending when the data is more accurate in predicting borrower performance. I also show that institutional lenders’ reduced demand for private information leads to less favorable loan terms for borrowers. Overall, these findings suggest that big data sources can crowd out the value of private information acquired through lending relationships.