(Informative)
Technical Specification: Compression and Understanding of Industrial data (MPAI-CUI) – Company Performance Prediction (CUI-CPP) V2.0 provides a solution to the problem of assessing the future of a company in terms of the prediction horizon, the efficacy of its governance, the probability of business interruption, the probability of company failure and an estimation of the factors affecting the governance, the discontinuity and the failure.
This goal is reached by providing a set of company-provided data, namely, financial statements, governance statements, and risk data. The last data are are grouped in two sets. The first, called Primary are fed to an an AI Model that complies with applicable regulations,. The second, called secondary, are fed to a data processing module.
The use of AI technologies allows the user to obtain a prediction for a much longer time horizon compared to classical statistical approaches such as Altman Z-score.
The reliability of the prediction greatly depends on how well the data used for training the model(s) are congruent with the economic context in which the company whose future is assessed.
The Chapters of CUI-CPP are normative unless they are explicitly labelled as Normative.
Capitalised Terms are defined by Table 1. All MPAI-defined Terms are accessible online.
