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• W2556449391 abstract "The balance sheet is a snapshot that portrays the financial position of a firm at a specific point in time. Under the reasonable assumption that the financial position of a firm is unique and representative, we use a basic artificial neural network pattern recognition method on Colombian banks' 2000–2014 monthly 25-account balance sheet data to test whether it is possible to classify them with fair accuracy. The results demonstrate that the chosen method is able to classify out-of-sample banks by learning the main features of their balance sheets, and with great accuracy. The results confirm that balance sheets are unique and representative for each bank, and that an artificial neural network is capable of recognizing a bank by its financial accounts. Further developments fostered by our findings may contribute to enhancing financial authorities' supervision and oversight duties, especially in designing early-warning systems." @default.
• W2556449391 created "2016-11-30" @default.
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• W2556449391 date "2017-09-01" @default.
• W2556449391 modified "2023-10-16" @default.
• W2556449391 title "Whose Balance Sheet Is This? Neural Networks for Banks' Pattern Recognition" @default.
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• W2556449391 doi "https://doi.org/10.1002/wilm.10619" @default.
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