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

By Jarl G. Kallberg, Gregory F. Udell. 2003

199 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/139d4be5f76a4d45b8f7fcd51d1e66a795fefd32

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Citations in the corpus

Credit Scoring and the Availability, Price, and Risk of Small Business Credit (2002, unknown): “One study found that credit scores based solely on business information (primarily trade credit data) generated by Dun and Bradstreet added significant explanatory power in predicting firm failure (Kallberg and Udell 2003).”
Credit Reporting, Relationship Banking, and Loan Repayment (2007, unknown): “Several authors have shown that credit reports do reduce the selection costs of lenders by allowing them to more accurately predict loan defaults (Kallberg and Udell, 2003; Barron and Staaten, 2003; Powell et al., 2004).”
Information Sharing and Credit: Firm-Level Evidence from Transition Countries (2009, background): “Analyses of credit bureau data confirm that credit reporting reduces the selection costs of lenders by allowing them to more accurately predict individual loan defaults (Barron and Staten, 2003; Kallberg and Udell, 2003; Powell, Miller, Mylenko, and Majnoni 2004; Luoto, McIntosh, and Wydick, 2004).”
When the Cat's Away the Mice will Play: Does Regulation at Home Affect Bank Risk Taking Abroad? (2013, unknown): “For example, age has been shown to be a highly statistically negative predictor of firm failure although firm size was not statistically significant in this study (Kallberg and Udell, 2003).”
Who Uses Financial Reports and for What Purpose? Evidence from Capital Providers (2014, unknown): “Kallberg and Udell (2003) provide a rare empirical analysis of the information used by credit bureaus when issuing their reports.”
Rules versus discretion in loan rate setting (2010, unknown): “Credit History Previous studies find that the history of the principal (e.g., Eisenbeis (1996), Berger, Frame and Miller (2005)) and third-party mercantile ratings (Kallberg and Udell (2003)) are very strong predictors of payment performance of small-business loans.”
Credit Line Usage, Checking Account Activity, and Default Risk of Bank Borrowers (2010, unknown): “We note that the question of how the value of account activity compares to the value of credit bureau information goes beyond the scope of this paper (for details see, e.g., Kallberg and Udell 2003).”
Bargaining power and information in SME lending (2010, methodology): “Furthermore, we consider the D&B credit score as hard information, since it is based on financial statements and payment information and does not include the variables EDU, EXPER, and AGE (e.g., Kallberg and Udell 2003 ).”
Alternative Information Sources and Information Asymmetry Reduction: Evidence from Small Business Debt (2015, background): “, bankruptcy proceedings, judgments, and suits), and (when provided by the firm) financial information on sales, net worth, and working capital (Kallberg and Udell, 2003).”
A More Complete Conceptual Framework for Financing of Small and Medium Enterprises (2005, background): “Commercial credit bureau data have also been shown to have power in predicting firm failure beyond financial ratios and other descriptive information about the firm (Kallberg and Udell 2003).”
The Past, Present, and Probable Future for Community Banks (2004, methodology): “15 For an analysis of the power of credit scoring as a business lending tool and the use of information exchange generated information in a credit scoring model see Kallberg and Udell (2003).”
Country Creditor Rights, Information Sharing and Commercial Banks Profitability Persistence across the world (2007, background): “4 Like Jappelli and Pagano (2002), Kallberg and Udell (2003) find evidence that formal information sharing contributes positively to the functioning of credit markets.”
A more complete conceptual framework for SME finance (2006, background): “Again, much of the difficulty in interpreting the results arises because the lending technologies are not identified. predicting firm failure beyond financial ratios and other descriptive information about the firm (Kallberg and Udell 2003).”