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Risk prevention of public procurement in the brazilian government using credit scoring

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  • Leonardo Sales

Abstract

Credit Scoring models are statistical applications used by financial institutions to classify applicants as to the possibility of becoming defaulters. This work aims to bring that good experience from the private sector to the governmental context, seeking to adapt it and test its performance in identifying bidders likely to fail in the fulfillment of obligations under contracts with the government. The results of methods based on different statistical techniques are compared. We hope to contribute to the preventive control of the contractual risks, both by the public manager as by the agencies of government control.

Suggested Citation

  • Leonardo Sales, 2013. "Risk prevention of public procurement in the brazilian government using credit scoring," OBEGEF Working Papers 019, OBEGEF - Observatório de Economia e Gestão de Fraude;OBEGEF Working Papers on Fraud and Corruption.
    • Handle: RePEc:por:obegef:019
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    File URL: http://www.fep.up.pt/repec/por/obegef/files/wp019.pdf
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    References listed on IDEAS

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    1. B Baesens & T Van Gestel & S Viaene & M Stepanova & J Suykens & J Vanthienen, 2003. "Benchmarking state-of-the-art classification algorithms for credit scoring," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(6), pages 627-635, June.
    2. D. J. Hand & W. E. Henley, 1997. "Statistical Classification Methods in Consumer Credit Scoring: a Review," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 523-541, September.
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