Neural Networks in Accounting: Clustering Firm Performance Using Financial Reporting Data

What is it about?

The present work is a research paper aiming at understanding if and how Neural Networks - and namely Kohonen's Self Organising Maps - could be useful to process financial data coming from annual financial reporting. Machine learning methods are promising techniques to process large amount of data and produce unknown relations and knowledge about business phenomena, however the specific application of these methods to financial reporting data are still to be deeply investigated. Respect to other works in the same field, the present paper better focalises the set of data, their features and it finally delivers a clearer understanding of the obtained results.

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