Public credit registries as a tool for bank regulation and supervision
This paper is about the importance of the information in Public Credit Registries (PCRs) for supporting and improving banking sector regulation and supervision, particularly in the light of the new approach embodied in Basel III. Against the backdrop of the financial crisis and the existence of information data gaps, the importance of complete, accurate and timely credit information in the financial system is evident. Both in normal times and during crises, authorities need a device that allows them to look at the universe of credits in a detailed and readily way. And more importantly, they need to develop tools that exploit as much as possible the information therein contained. PCR databases contain individual credit information on borrowers and their credits which makes it possible to implement advanced techniques that measure banks'credit risk exposure. It allows optimizing the prudential regulation ensuring that provisioning and capital requirements are properly calibrated to cover expected and unexpected losses respectively. It also permits validating banks'internal rating systems, performing stress tests and informing macroprudential surveillance. In this respect, it is envisioned that the existence of a PCR will be a key factor to enhance the supervision and regulation of the financial system. Furthermore, the extent, accuracy and availability of the information collected by the authorities will determine the usefulness of the PCR as part of their toolkit to monitor the potential vulnerabilities not only on a microprudential level, but also on a macroprudential one.
|Date of creation:||01 Dec 2010|
|Date of revision:|
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- Ricardo Schechtman & Valéria Salomão Garcia & Sergio Mikio Koyama & Guilherme Cronemberger Parente, 2004. "Credit Risk Measurement and the Regulation of Bank Capital and Provision Requirements in Brazil - A Corporate Analysis," Working Papers Series 91, Central Bank of Brazil, Research Department.
- Gutierrez Girault, Matias, 2006. "Non – parametric estimation of conditional and unconditional loan portfolio loss distributions with public credit registry data," MPRA Paper 9798, University Library of Munich, Germany, revised Jun 2007.
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