The value of private sector business credit information sharing: The US case

Abstract

This paper investigates the value added by private information exchanges that share information on business payment performance. We discuss how this information is collected and disseminated by the world’s largest private information broker, Dun & Bradstreet. We provide the first empirical examination of the importance of this information at the lending decision level. Our findings indicate that exchange-generated information provides significant explanatory power in failure prediction models controlling for other credit information that is easily available to lenders. Our study complements the work of Jappelli and Pagano [Information sharing, lending and defaults; Cross country evidence, Centre for Economic Policy Research, Discussion Paper 2184, 1999] who find in cross-country macro level tests that information exchanges add value.

Introduction

The extension of business credit is problematic because of the information wedge between lenders and borrowers. Informational opacity significantly affects business access to external finance and its cost, particularly for smaller companies. These firms are excluded from public debt and equity markets and are substantially dependent on private debt markets for external finance.¹ These private debt markets employ an extensive array of mechanisms to solve information problems. Efforts by financial economists to explain these solutions have led to the modern information-based theory of financial intermediation and have provided the theoretical motivation of contractual tools such as collateral, guarantees, covenants and maturity.

One very important market tool has been ignored in the academic literature until quite recently – the exchange of credit information by lenders, particularly through formal exchange mechanisms. The paucity of research in this area is remarkable given the widespread use of formal information exchanges. Information exchanges can be formalized in one of two ways: (i) an exchange mechanism imposed by government regulation, or (ii) a voluntary exchange mechanism. Regulation-imposed exchange mechanisms often take the form of “public credit registers” managed by central banks. Under these programs information reporting is compulsory. Voluntary exchange mechanisms can take the form of cooperatives or private information exchanges, such as the world’s largest: the Dun & Bradstreet Corporation (D&B).

One of the goals of our paper is to empirically explore the value of business-to-business voluntary information exchange mechanisms using the US as an example. We focus exclusively on the commercial credit market and the associated business-to-business exchange of credit information by examining two fundamental questions.² First, is the formal exchange of business credit information valuable to creditors when they conduct their borrower due diligence? Second, does the value of this information extend beyond just the efficient dissemination of otherwise readily available information? We address these questions by analyzing the power of exchange-generated information in assessing borrower quality. Specifically, we empirically test the hypothesis that exchange-generated information is a significant explanatory variable in a firm failure prediction model controlling for information that would normally otherwise be available to a commercial lender, such as firm characteristics and financial statement data. We use a database from D&B that allows us to analyze these questions at the credit decision making level, i.e., at the borrowing-firm level.

Our analysis complements and extends the empirical work of Jappelli and Pagano (1999) who also empirically address the issue of the value of formal information exchanges. In particular, they use a macro approach to analyze the cross-country association between the presence of formal information exchanges and measures of aggregate economic performance. Like Jappelli and Pagano (1999), we find evidence consistent with the proposition that formal information sharing contributes positively to the functioning of credit markets. Our approach, however, is quite different from theirs. We are the first to take a micro approach by analyzing the value of information exchange-generated information at the credit decision-making level.

Our focus on the US may be particularly interesting because the market for business-to-business information exchange is dominated by one company, the world’s largest formal information exchange, D&B. A secondary objective of this paper is to describe how formal information exchanges like D&B operate. It is generally accepted that formal credit information sharing is characterized by significant economies of scale (e.g., Pagano and Jappelli, 1993). Therefore, it may be particularly interesting to analyze the collection, dissemination, and value of information generated by the organization that is likely the most scale-efficient information exchange.

By analyzing a private business information exchange we also shed light on a related issue. Voluntary private information exchanges differ in some important ways from public credit registries. One difference is coverage. Participation in public credit registers is typically compulsory, which means that suppliers of credit (e.g., banks, finance companies, trade creditors) are obligated to furnish payment performance information on their customers/borrowers. This is decidedly not the case with private information exchanges.³ Specifically, credit suppliers will only share information with a private information exchange to the extent that it is in their financial interest to do so. Thus, the value of information provided by information exchanges will depend on the extent to which they can profitably offer incentives that encourage sufficient coverage.

It is also possible that collection bias in the data diminishes the quality of the information provided by information exchanges. For example, smaller credit issuers may be under-represented in an exchange’s database. This may be problematic if business financial distress manifests itself in slowness in paying smaller creditors before it is reflected in slowness in paying larger creditors. Arguably the problems of coverage and bias may be more acute in voluntary information exchanges than public credit registries.⁴ Finally, all information exchanges must solve a credibility problem. That is, like all financial intermediaries they must convince their customers that their information is reliable. Arguably, public information exchanges, which are often run by central banks, have an advantage in this regard. Our finding that the information generated by a private information exchange is significantly informative, suggests that these credibility problems are solvable.

Our paper is organized as follows. We begin our analysis with an overview of the relevant literature on the economics of information sharing. We also examine the extent to which this literature makes a distinction between public credit registers and voluntary information exchanges. In Section 3 we examine business information sharing in the US, focusing on the dominant player, D&B. D&B has collected information on over 70 million businesses in over 219 countries (D&B, 2002). Because formal information exchange has received so little attention in the academic literature we provide some detail on D&B’s production process and the specific nature of its output. In Section 4, we empirically examine the value of D&B’s business credit information by analyzing its power in failure prediction models. Specifically, we analyze whether exchange-generated information available one year prior to a success/failure outcome is significant in discriminating between failed and non-failed firms controlling for other information that would have been readily available to creditors to predict success. We construct a sample of firms in the retail industry that failed over a one-year period, and a sample of comparable firms that survived (i.e., were in existence one year later). To be included in the sample, sufficient information about the firm’s financial condition and exchange-generated information about the firm had to be available prior to the success/failure outcome. Our selection criteria produced a sample of 241 failed firms and 2482 non-failed firms. We offer concluding comments in Section 5.