Collateral, type of lender and relationship banking as determinants of credit risk

By Gabriel Jiménez, Jesús Saurina. 2004

436 citations recorded by the source corpus.

This paper analyses the determinants of the probability of default (PD) of bank loans. We focus the discussion on the role of a limited set of variables (collateral, type of lender and bank borrower relationship) while controlling for the other explanatory variables. The study uses information on the more than three million loans entered into by Spanish credit institutions over a complete business cycle (1988 to 2000) collected by the Bank of Spain's Credit Register (Central de Informacion de Riesgos). We find that collateralised loans have a higher PD, loans granted by savings banks are riskier and, finally, that a close bank borrower relationship increases the willingness to take more risk.

Subfields: Accounting, Finance

View Paper: https://www.semanticscholar.org/paper/5517617e43d988218ac0946f892234e44ee1cf72

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Accounting

In Finance

Citations in the corpus

Determinants of Default in P2P Lending (2015, background): “Empirical studies show ambiguous results, with none of them being significant [61], [62].”
Determinants of Collateral (2004, positive): “Finally, Jimenez and Saurina (2004), with the same database used in this paper but with the stock of loans not with the new loans in each period, find that the presence of collateral increases the likelihood that a loan will be in default, but no distinction is made as a function of the age of the…”
Recovery Rates of Commercial Lending: Empirical Evidence for German Companies (2009, neutral): “35 However, Jiménez and Saurina (2004) determine that for Spanish companies banks are more frequently willing to take higher credit risk if the client relationship is strong.”
Does Collateral Help Mitigate Adverse Selection? A Cross-Country Analysis (2011, neutral): “Former studies on the role of collateral in solving ex ante information asymmetries, like Jimenez and Saurina (2004), also do not consider borrower characteristics and rather focus on loan characteristics.”
Business models and bank performance: a long-term perspective (2016, background): “This may also enable retail-oriented banks to more adequately price and monitor credit risk, for instance through a greater emphasis on relationship banking (Boot, 2000; Jiménez and Saurina, 2004).”
A Lender-Based Theory of Collateral (2007, positive): “…and Sharpe, 2000), and–controlling for observable borrower risk–collateralized loans appear to be riskier in the sense that they default more often (Jiménez and Saurina, 2004; Jiménez, Salas, and Saurina, 2005) and have worse performance in terms of payments past due and non-accruals (Berger and…”
COLLATERAL AND CREDIT RATIONING: A REVIEW OF RECENT EMPIRICAL STUDIES AS A GUIDE FOR FUTURE RESEARCH (2009, positive): “In addition, the introduction of competition between banks will dilute any informational rents since each bank will thoroughly screen the firm in order to secure the repayment of the loan (Jiménez and Saurina, 2004).”
Organizational distance and use of collateral for business loans (2009, background): “Jiménez, Salas and Saurina (2006) provide empirical evidence that supports this first prediction, and Jiménez and Saurina (2004) confirm that collateralized loans are ex post riskier than non-collateralized loans.”
Market power, revenue diversification and bank stability: Evidence from selected South Asian countries (2012, background): “The impact of bank market power on net interest margins (Maudos and Fernández-de-Guevara, 2004), on financial stability (Jiménez and Saurina, 2004; Agoraki et al., 2011), on bank efficiency (Delis and Tsionas, 2009; Turk-Ariss, 2010) and on bank regulations (Beck et al., 2006; Fonseca and González,…”
How do lending relationships affect access to credit and loan conditions in microlending (2011, neutral): “7 Other measures for the length and intensity of the relationship used in the literature are the amount of different banking services offered and requested (Petersen and Rajan, 1994), the distance between bank and borrower in miles/kilometers (Degryse and Ongena, 2005; Agarwal and Hauswald, 2007), w”
Credit Risk Drivers: Evaluating the Contribution of Firm Level Information and of Macroeconomic Dynamics (2009, positive): “This evidence helps to support the hypothesis that most credit risk is built up during periods of strong credit growth, materialising only when the economy hits a downturn, as discussed above (see Pederzoli and Torricelli (2005) or Jiménez and Saurina (2006), for instance).”