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The Validation of AI Techniques

In: Artificial Intelligence and Credit Risk

Author

Listed:
  • Rossella Locatelli

    (University of Insubria)

  • Giovanni Pepe

    (KPMG Advisory)

  • Fabio Salis

    (Credito Valtellinese)

Abstract

This chapter describes the implementation of validation techniques aimed at monitoring and mitigate risks related to the development of AI models. The key trustworthy indicators are identified and detailed in coherence with the main trustworthy principles, namely accuracy, robustness, fairness, efficiency and explainability. Also, a focus on the interpretability of the AI models’ outcomes, summarising the main regulatory requirements, and describing the methodological approaches aimed at assessing the stability of the models is detailed. In order to evaluate and interpret the results of the AI models, the contribution of each risk divers is assessed by means of specific methodologies.

Suggested Citation

  • Rossella Locatelli & Giovanni Pepe & Fabio Salis, 2022. "The Validation of AI Techniques," Springer Books, in: Artificial Intelligence and Credit Risk, chapter 0, pages 65-79, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-10236-3_4
    DOI: 10.1007/978-3-031-10236-3_4
    as

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