So what do I get? The bank's view of lending relationships

Abstract

While a number of empirical studies have documented benefits of lending relationships to borrowers (lower loan rates, better credit availability, etc.), not much is known about benefits of such relationships for lenders. For a relationship lender, its comparative advantage in information gathering/processing yields two potential benefits. First, a relationship lender would have a higher probability of selling future information-sensitive products (e.g. loans, security underwriting, etc.) to its borrowers compared to a non-relationship lender. We refer to this as higher volume benefit of relationship lending. Second, if borrower-specific information is only available to relationship lender, it can use this information monopoly to charge higher rates on future loans. We refer to this as increased pricing benefit of relationship lending. Our results show that, on average, a lender with a past relationship with a borrower has a 42% probability of providing it with future loans, while a lender lacking a past relationship with a borrower has only a 3% probability of providing it with a future loan. Consistent with theory, we find that borrowers with greater information asymmetries (e.g. small borrowers, or non-rated borrowers) are significantly more likely to use their relationship banks for future loans. Although the association between past lending relationship and probability of being chosen to provide debt and equity underwriting services in the future is statistically significant, the economic impact is much smaller compared to loan markets. However, our findings do not provide strong support for an increased pricing benefit for relationship lenders. On average, the rate of interest for similar borrowers is 6-10 basis points lower if the loan is provided by a relationship lender. Underwriting fee for initial public offerings (IPO) with relationship lender(s) as lead underwriter(s) is 26 basis points lower. This suggests that lenders are prepared to share some of the benefits of relationship lending with borrowers. * Bharath is with University of Michigan, Dahiya is with Georgetown University, Saunders is with New York University, and Srinivasan is with University of Georgia. Dahiya acknowledges the support of the Lee Higdon, Jr. So What Do I Get? The Bank's View of Lending RelationshipsAbstract While a number of empirical studies have documented benefits of lending relationships to borrowers (lower loan rates, better credit availability, etc.), not much is known about benefits of such relationships for lenders. For a relationship lender, its comparative advantage in information gathering/processing yields two potential benefits. First, a relationship lender would have a higher probability of selling future information-sensitive products (e.g. loans, security underwriting, etc.) to its borrowers compared to a non-relationship lender.We refer to this as higher volume benefit of relationship lending. Second, if borrowerspecific information is only available to relationship lender, it can use this informatio...

The Costs of Being Private: Evidence from the Loan Market

“…6 6 The more recent banking and corporate nance literature uses propensity score matching to correct for self selection bias. Bharath, Dahiya, Saunders, and Srinivasan (2008) use propensity score matching to identify the impact of lending relationships on loan spreads and Drucker and Puri (2005) assess the impact of bundling of investment banking and commercial banking services on loan spreads. Michaely and Roberts (2007) apply propensity score matching to a large set of UK companies.…”

“…Prior research documents the importance of informational transparency in explaining loan spreads (Santos and Winton (2008), Bharath, Dahiya, Saunders, and Srinivasan (2008) and Schenone (2007))). We nd supporting evidence for this hypothesis.…”

“…(Lee and Mullineaux (2004), Jones, Lang, and Nigro (2005), Su (2007)) How are syndicated loans priced? (Bharath, Dahiya, Saunders, and Srinivasan (2007), Bharath, Dahiya, Saunders, and Srinivasan We employ three di erent measures of information opacity to measure loan cost di erences between private and public borrowers. More speci cally, we use: (i) stock exchange a liation, (ii) analyst coverage, and (iii) listing among the Fortune 500 rms, as proxies for information opacity.…”

Why Do Firms Switch Banks? Evidence from China

“…The conclusion is that small banks have a comparative advantage in processing soft information and delivering relationship lending. Bharath et al (2007) measures the direct benefit to the bank from relationship banking. They find that the degree of information asymmetry increased the likelihood of banks winning the borrower's future loan contract.…”

Bankruptcy choice with endogenous financial constraints

“…Studying dynamic contracts is important because there is growing evidence that long-term credit relationships are particularly attractive for small and opaque firms (Bharath et al (2007(Bharath et al ( , 2011). Moreover, renegotiations and state contingency -salient features of dynamic contracts-appear to be norm in actual financial contracting (Roberts and Sufi (2009)).…”