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This paper introduces a model for rating a firm's default risk based on fuzzy logic and expert system and an associated model of sensitivity analysis (SA) for managerial purposes. The rating model automatically replicates the evaluation process of default risk performed by human experts. It makes use of a modular approach based on rules blocks and conditional implications. The SA model investigates the change in the firm's default risk under changes in the model inputs and employs recent results in the engineering literature of Sensitivity Analysis. In particular, it (i) allows the decomposition of the historical variation of default risk, (ii) identifies the most relevant parameters for the risk variation, and (iii) suggests managerial actions to be undertaken for improving the firm's rating. [ABSTRACT FROM AUTHOR]

This paper presents a real-life application of a fuzzy expert system aimed at rating and ranking firms. Unlike standard Discounted Cash Flow (DCF) models, it integrates financial, strategic and business determinants and processes both quantitative and qualitative variables.Twenty-one value drivers are defined concerning the target firm (strategic assets in place and prospective financial performance), the acquisition (synergies, quality of management) and the sector (intensity of competition, entry barriers). Their combination via 'if-then' rules leads to the definition of an output represented by a real number in the interval (0, 1). Such a number expresses the value-generating power of the target firm inclusive of synergies with the bidder (here named Strategic Enterprise Value). The system may be used for rating and ranking firms operating in the same sector. A regression analysis, using hostile takeover multiples, may be employed to translate the score into price. The real-life case refers to Camuzzi, a natural gas distributor, acquired by Enel, the Italian ex-monopolist of electric energy. [ABSTRACT FROM AUTHOR]