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Banking practices and borrowing firms’ financial reporting quality: evidence from bank cross-selling

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Abstract

This paper studies whether banking practices affect borrowing firms’ financial reporting quality. Specifically, I examine the effect of bank cross-selling activities (i.e., a bank’s joint provisions of lending and underwriting services to the same firm) on borrowers’ financial reporting quality for debt contracting purposes. Compared to issuing stand-alone loans, cross-selling increases a bank’s risk exposure to the firm and therefore gives the bank more motivation to monitor the borrower’s financial condition (incentive effect). In addition, cross-selling enables information sharing between the underwriting and lending divisions and allows the bank to have a closer understanding of the borrower’s underlying economics, which disciplines the borrower’s ability to withhold bad news (information effect). Consistent with these arguments, I expect and find that cross-selling is associated with an improvement in the debt contracting value (DCV) of accounting information at borrowing firms. I also provide evidence in support of the incentive effect and the information effect.

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Notes

  1. Their rationale is that breaking up universal banks can help solve the “too big to fail” problem and thus protect taxpayers from having to bail out banks due to their excessive risk-taking in nontraditional bank activities. For example, the 21st-Century Glass-Steagall Act was introduced to Congress in 2013, 2015, and 2017.

  2. Banks face additional risks associated with underwriting services: potential losses of business or legal liabilities as a result of failures to perform due diligence (e.g., Beatty and Ritter 1986; Chemmanur and Fulghieri 1994). Anecdotally, in one of the largest class-action settlements ever, Citigroup Inc. agreed to pay $2.65 billion to settle a suit brought by WorldCom investors. The lawsuit alleges that Citigroup and other investment banks did not conduct adequate due diligence before bringing WorldCom bonds to the market in May 2000 and May 2001. See http://www.nytimes.com/2004/05/11/business/citigroup-agrees-to-a-settlement-over-worldcom.html?_r=0 for details. In addition, Blackwell et al. (1990) suggest that the reason we observe so few due diligence cases reaching court is the sensitivity of the value of the underwriters’ reputation to adverse publicity.

  3. It is beyond the scope of this paper to assess whether returning to the Glass-Steagall separation would reduce social welfare overall. The findings that banks’ increase in monitoring in the case of cross-selling help alleviate the concern that allowing banks to cross-sell will create conflicts of interest and thus lead to greater loan default risks.

  4. Please see https://www.warren.senate.gov/files/documents/2017_04_06_21st_Century_Glass_Steagall_Act.pdf for details.

  5. The Volker rule is amended on June 25, 2020 and is effective on October 1, 2020.

  6. The empirical literature in this area finds little support for banks’ exploiting of conflicts of interest. Instead, most studies find that cross-selling improves the certification ability of commercial banks.

  7. Under the Anti-Tying Provision, a bank cannot require the borrower to purchase another product from the bank or its affiliate in exchange for a loan; therefore, coercive impositions are rarely found (Chang, 2012). Yet, voluntary ties are found to be common as the client realizes that it stands a better chance of obtaining the desired product (i.e., loans) by “volunteering” to accept the tied product (i.e., underwriting services). I further discuss firms’ incentives to accept the tied product in Sect. 5.3.3. In 2004, the Association of Financial Professionals (AFP) conducted a survey of 370 corporate financial executives, and 96% of the executives said that they had been pressured by lenders to buy underwriting or other services when obtaining loans. Nearly two-thirds of the respondents had been denied credit or had their loan prices raised after their company did not give their banks additional services.

  8. I also use the Freedom of Information Act to obtain the historical Fed approval dates of the Sect. 20 subsidiaries to cross-check my matching of the underwriter and the lender.

  9. The details of this deregulation can be found on the website https://www.federalreserve.gov/boarddocs/press/ boardacts/1997/19970822/R-0958.pdf.

  10. Based on previous studies (e.g., Black et al. 2004; Vasvari 2010), one reason for eliminating financial firms in this context is that debt covenants for these firms are redundant. Regulatory monitoring is more efficient than covenants; therefore, financial institutions that borrow have fewer covenants for this external reason.

  11. In such cases, I use the total loan amount, the average loan maturity, and the average interest spread for the loan characteristics used in Model (1) introduced in Sect. 4.2.

  12. These observations represent 3,183 firm-cross-sold loan initiation years and 2,781 firm-non-cross-sold loan initiation years. Dealscan includes both loan originations and loan amendments. Loan amendments refer to cases where loans are refinanced or amended to increase loan amount, change loan maturity, or modify other loan characteristics (e.g., change from a revolving loan to a term loan). I do not distinguish loan amendments from my loan originations because the same arguments also apply to loan amendments.

  13. Other studies provide different measures of debt contracting values at the industry level. For example, Ball et al. (2008) use the ability of changes in quarterly accounting earnings to predict credit quality downgrades (Somer’s D from the Probit regression). Christensen and Nikolaev (2011) measure the ability of levels of accounting variables to predict credit qualities (pseudo R2 from the ordered Logit regression). These industry-level measures are less suitable in my context because firms within the same industry could be cross-sold loan recipients and non-cross-sold loan recipients.

  14. I use the same sample as in Table 6 for consistency and therefore require the loans to have nonmissing data for the borrower incentive analysis. If I do not impose this restriction and use a larger sample instead, the inferences remain the same.

  15. The number of observations in this analysis is lower than in the main test due to missing data for lead lenders’ shares in Dealscan. The final sample includes 16,129 observation in total (representing 1,152 unique firms).

  16. I only use the underwriting amount in SDC but not FISD to calculate the underwriting amount to avoid double-counting. The final sample includes 31,138 observations in total (representing 1,833 unique firms).

  17. The results are similar if I use a two-year window.

  18. The difference in the coefficient on PostLoan × CrossSoldLoan × ROA in columns 1 and 2 is marginally significant (P-value = 0.06, one-sided), as I have a directional prediction in this test.

  19. The incentive effect also exists in this period. However, the information effect is limited during this period due to the mandated information firewall, so I do not find positive results as using the post-deregulation sample. The results here should be interpreted with caution because cross-selling is not common in the pre-deregulation period. For the sample in Table 5, the mean of CrossSold is 8%, compared to 53% for the main sample.

  20. The baseline regression in Basu (1997) is as follows: \(EPS ={\beta }_{0}+{\beta }_{1}DRet+{\beta }_{2}Ret+{\beta }_{3}DRet\times Ret\). Timely loss recognition refers to the greater timeliness of earnings with respect to negative returns relative to positive returns. Therefore, β3 is greater when loss recognition is more timely. I expand this model by introducing two indicator variables – CrossSold and PostLoan – to compare the change in TLR for cross-sold loan recipients versus non-cross-sold loan recipients upon the receipt of the loan. In the modified regression, I expect the coefficient on DRet × Ret × PostLoan × CrossSold to be positive.

  21. I hold firm financing activities constant by requiring both the treatment and control samples to be associated with loans that are issued around public security issues.

  22. I identify lead arrangers using the LeadArrangerCredit variable in Dealscan. In cases where lead arrangers are not identified, I follow Standard & Poor’s A Guide to the Loan Market (October 2007) and Cai (2010) to classify lenders as lead arrangers if their lender titles are among the following: administrative agent, agent, arranger, bookrunner, coordinating arranger, lead arranger, lead bank, lead manager, and mandated arranger. Using this definition, 83% (68%) of cross-sold loans (non-cross-sold loans) have at least two lead arrangers.

  23. General covenants are nonfinancial covenants including equity issuance sweeps, debt issuance sweeps, asset sales sweeps, insurance proceeds sweeps, and dividend restrictions.

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Acknowledgements

This paper is based on my Ph.D. dissertation at the University of Toronto. I would like to thank my thesis committee members Scott Liao (co-chair), Gordon Richardson (co-chair), Dushyant Vyas, and Baohua Xin for their invaluable guidance and support. I also appreciate comments from Jeff Callen, Gus De Franco, Alex Edwards, Carlo Gallimberti (discussant), Yadav Gopalan, Elizabeth Gordon, Ole-Kristian Hope, Yu Hou, Zeqiong Huang, Daehyun Kim, Yun Lee (discussant), Partha Mohanram, Tathagat Mukhopadhyay, Catherine Schrand, Colin Tipton, Franco Wong, and the participants at the AAA Annual Meeting, the London Business School Trans-Atlantic Doctoral Conference, University of Toronto, University of Missouri, London School of Economics, Temple University, and Nanyang Technology University. I thank Jae Kim and Kelvin Luo for their excellent research assistance. Any remaining errors are my own.

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    Barbara Su

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Appendices

Appendix A

Table 10 Evolution of major regulations or proposed regulations on the scope of bank activities
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Appendix B

Table 11 Variable definitions
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Su, B. Banking practices and borrowing firms’ financial reporting quality: evidence from bank cross-selling. Rev Account Stud 28, 201–236 (2023). https://doi.org/10.1007/s11142-021-09640-6

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