Modeling logic and neural approaches to bankruptcy prediction models

The guiding principle of process automation and soft computing is to achieve more robust, traceable and low cost solutions which incorporate the required intelligence to information technologies, thus enabling human centered functionalities. The application of Artificial Intelligence (IA) and Neural systems to the financial and banking industries has performed well in the areas of Risk Management improvement and Bankruptcy prediction. This paper contributes to analyze the synergies between logic and neural based approaches as the basis to enhance bankruptcy prediction models development.