Accounting Information Inconsistencies and Their Effects on Insolvency Prediction Models

23 Pages Posted: 11 Mar 2010

See all articles by Ricardo Lopes Cardoso

Ricardo Lopes Cardoso

Brazilian School of Public and Business Administration; Rio de Janeiro State Univ., FAF

Alexandre Mendes

affiliation not provided to SSRN

Poueri do Carmo Mário

FACE/UFMG

Antonio Lopo Martinez

University of Coimbra; Department of Federal Revenue of Brazil

Felipe Ramos Ferreira

EBAPE/FGV

Date Written: March 8, 2010

Abstract

Many studies have shown that avoiding political costs is an incentive for firms to manipulate accounting information, e.g., McNichols and Wilson, 1988; Jones, 1991; Kato et al., 2001. The majority of them use discretionary accruals models as proxies to manipulation. This paper introduces a new variable (DIF) that measures data inconsistencies present in financial reports, replacing discretionary accruals in the detection of manipulation. Accounting information was collected from 2,033 Brazilian health maintenance organizations (HMOs). This information was then processed and financial ratios derived from insolvency prediction models and thresholds established by the regulatory agency were taken as attributes to differentiate solvent HMOs from insolvents. During this data processing, inconsistencies were identified and instead of being removed, were used to determine the value of the attribute DIF. Processed data was then analysed using data mining techniques and a series of classifiers were created. The classifiers found have high accuracy in terms of discriminating distressed companies, especially when the DIF variable is used. In addition, the attributes selected and the structure of the classifiers can be supported by traditional models of analysis based on financial ratios. Results are relevant for those who are interested in assessing firms’ insolvency risk, because data inconsistencies may signal firms’ performance, therefore shall not be removed from analysis.

Keywords: insolvency, inconsistency, earnings management, health maintenance organization

JEL Classification: M41, G33, G22, C81

Suggested Citation

Cardoso, Ricardo Lopes and Mendes, Alexandre and Mário, Poueri do Carmo and Martinez, Antonio Lopo and Ferreira, Felipe Ramos, Accounting Information Inconsistencies and Their Effects on Insolvency Prediction Models (March 8, 2010). Available at SSRN: https://ssrn.com/abstract=1567754 or http://dx.doi.org/10.2139/ssrn.1567754

Ricardo Lopes Cardoso (Contact Author)

Brazilian School of Public and Business Administration ( email )

Rua Jornalista Orlando Dantas, 30
Office 206. Botafogo
Rio de Janeiro, Rio de Janeiro 22231-010
Brazil
+55-21 30832713 (Phone)

Rio de Janeiro State Univ., FAF ( email )

Rua Sao Francisco Xavier, 524
bloco B, sala 1024
Rio de Janeiro, Rio de Janeiro
Brazil

Alexandre Mendes

affiliation not provided to SSRN ( email )

Poueri do Carmo Mário

FACE/UFMG ( email )

Brazil
+55 31 34097267 (Phone)
+55 31 34097267 (Fax)

Antonio Lopo Martinez

University of Coimbra ( email )

Pátio das Escolas
Coimbra
Portugal

Department of Federal Revenue of Brazil ( email )

Brazil

Felipe Ramos Ferreira

EBAPE/FGV ( email )

Brazil
+55 21 37995781 (Phone)
+55 21 37995710 (Fax)

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