Which Characteristics Predict the Survival of Insolvent Firms? An SME Reorganization Prediction Model

Authors

  • Maria-del-Mar Camacho-Miñano,

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    • Address correspondence to: Maria-del-Mar Camacho-Miñano, School of Business Administration and Economics, Department of Financial Economics and Accounting II (Accounting), Campus of Somosaguas, Complutense University of Madrid, Campus of Somosaguas, 28223 Pozuelo-de-Alarcón, Madrid, Spain. E-mail: marcamacho@ccee.ucm.es.

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    • Maria-del-Mar Camacho-Miñano is assistant professor at Department of Financial Economics and Accounting II, Complutense University of Madrid.
  • Maria-Jesus Segovia-Vargas,

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    • Maria-Jesus Segovia-Vargas is assistant professor at Department of Financial Economics and Accounting I, Complutense University of Madrid.
  • David Pascual-Ezama

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    • David Pascual-Ezama is assistant professor at Department of Financial Economics and Accounting II, Complutense University of Madrid.

Abstract

The negative impact of insolvency, especially in small and medium enterprises, informs the objective of this paper: to study the characteristics of bankrupt firms to achieve a preventive diagnosis for reorganization by means of artificial intelligence (AI) methodologies such as rough set and PART methods. The AI models obtained show not only the key variables to predict insolvency, but also their relations and the critical values. Using only five firm characteristics (sector, size, number of shareholdings, return on assets, and cash ratio), our model could reduce delays and costs, since it is able to predict which firms will undergo reorganization or liquidation before the legal procedure.

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