The Company Performance Prediction (CUI‑CPP) V2.0 standard provides a solution for assessing the future performance of a company over a specified prediction horizon.

The standard evaluates the impact of risks of different natures on key aspects such as:

  • Effectiveness of company governance.
  • Probability of business discontinuity.
  • Probability of company failure.
  • Relevant factors identified as influencing those values.

CUI‑CPP enables advanced analysis based on AI technologies, allowing predictions over significantly longer time horizons as compared to traditional statistical methods.

The Reference Model

CUI‑CPP is based on a composite AI Module that includes interoperable AI Modules operating within the MPAI Artificial Intelligence Framework (MPAI‑AIF). Based on pre-processing company data to extract descriptors specified by the standard, the system generates predictive indicators.

The model relies on four main categories of input data:

  • Financial Descriptors
  • Governance Descriptors
  • Primary Risk Descriptors
  • Secondary Risk Statements

Primary Risk Descriptors (e.g., climate and cyber risks) are processed by AI models compliant with applicable regulations, while Secondary Risk Statements are handled by dedicated data processing modules.

Prediction Process

The system analyses the input data over a specified Prediction Horizon to produce a set of standardised outputs describing the company’s expected performance.

Key outputs include:

  • Organisation Descriptors indicating their impact on default probability and relevant governance factors.
  • Primary Default Descriptors including default probability and key contributing factors.
  • Primary Discontinuity Descriptors describing risks that could cause operational disruption.
  • Secondary Discontinuity Probability indicating the general likelihood of business interruption.

This structured output provides a clear and interpretable representation of the company’s risk profile.

Data and AI Models

CUI‑CPP uses AI models trained on datasets reflecting specific economic contexts. The reliability of predictions depends on the alignment between training data and the company being assessed.

The standard currently defines:

  • Financial and Governance risks
  • Climate risk descriptors
  • Cyber risk descriptors

The framework allows extension to additional risk categories, using the same methodology, to support future evolution of the standard.

Powered by the MPAI AI Framework

CUI‑CPP operates within the MPAI Artificial Intelligence Framework (MPAI‑AIF), which provides a standard execution environment based on modular and interoperable AI components (AI Modules).

AI Modules are dynamically configured and executed exchanging standard Data Types, enabling flexible and scalable implementations.

Open and Flexible Design

CUI‑CPP follows key design principles:

  • Modular components with well‑defined interfaces.
  • Separation of data processing and AI modelling.
  • Support for standard and extensible risk categories.
  • Independence from specific implementation technologies.

This enables independent development of components while maintaining interoperability.

Benefits

The CUI‑CPP standard supports:

  • Financial analysts to assess company risk with advanced AI tools.
  • Organisations to evaluate their exposure to multiple types of risk.
  • Developers to build interoperable risk analysis applications.
  • Regulators to rely on transparent and structured assessment methods.
  • Markets to benefit from more reliable and comparable company evaluations.

By enabling transparent and explainable analysis, the standard improves trust in AI‑based financial predictions.

A New Paradigm for Risk Assessment

CUI‑CPP promotes a shift from traditional statistical models to:

  • AI‑based predictive analysis
  • Multi‑factor risk evaluation
  • Standardised and interpretable outputs

This approach enables deeper insight into the drivers of company performance and risk.

Conclusion

MPAI CUI‑CPP V2.0 provides a complete and interoperable framework for company performance prediction that:

  • Integrates financial, governance, and risk data
  • Supports AI‑based long‑term prediction
  • Delivers structured and explainable results
  • Enables extensibility to new risk domains

The standard opens the way to a new generation of transparent, AI‑driven tools for corporate risk assessment and decision making.