An artificial neural network approach for assigning rating judgements to Italian Small Firms

Greta Falavigna

CERIS Working Paper from CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY

Abstract: Based on new regulations of Basel II Accord in 2004, banks and financial nstitutions have now the possibility to develop internal rating systems with the aim of correctly udging financial health status of firms. This study analyses the situation of Italian small firms that are difficult to judge because their economic and financial data are often not available. The intend of this work is to propose a simulation framework to give a rating judgements to firms presenting poor financial information. The model assigns a rating judgement that is a simulated counterpart of that done by Bureau van Dijk-K Finance (BvD). Assigning rating score to small firms with problem of poor availability of financial data is really problematic. Nevertheless, in Italy the majority of firms are small and there is not a law that requires to firms to deposit balance-sheet in a detailed form. For this reason the model proposed in this work is a three-layer framework that allows us to assign ating judgements to small enterprises using simple balance-sheet data.

Keywords: rating judgements; artificial neural networks; feature selection (search for similar items in EconPapers)
JEL-codes: C15 C45 G24 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2011-06
New Economics Papers: this item is included in nep-ban, nep-cmp and nep-rmg
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