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Financial distress of municipalities, although comparable to bankruptcy ofprivate companies, has a far more serious impact on the well-being ofcommunities. For this reason, it is essential to detect deficits as soon aspossible. Predicting financial distress in municipalities can be a complextask, as it involves understanding a wide range of factors that can affect amunicipality's financial health. In this paper, we evaluate machine learningmodels to predict financial distress in Italian municipalities. Accountingjudiciary experts have specialized knowledge and experience in evaluating thefinancial performance, and they use a range of indicators to make theirassessments. By incorporating these indicators in the feature extractionprocess, we can ensure that the model is taking into account a wide range ofinformation that is relevant to the financial health of municipalities. Theresults of this study indicate that using machine learning models incombination with the knowledge of accounting judiciary experts can aid in theearly detection of financial distress, leading to better outcomes for thecommunities.

Predicting municipalities in financial distress: a machine learning approach enhanced by domain expertise