AI can make the relative-valuation process sess subjective

Abstract

This article presents a new methodology for relative valuation that incorporates artificial intelligence. The methodology uses AI to review historical data—such as revenues, earnings, and debt levels—to detect patterns and relationships related to historical valuations that traditional methods might miss. By integrating AI into the relative-valuation process, organizations can transform a traditionally subjective art into a more rigorous, transparent, and data-driven science. The process not only enhances valuation accuracy but also builds confidence among stakeholders by clearly showing the rationale behind each valuation decision. As a case study, the authors apply their methodology to Mastercard, analyze the results, and then recommend four key steps that companies should take if they are looking to integrate AI into valuatio

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Last time updated on 07/07/2025

This paper was published in Vlerick Repository.

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