Using Artificial Intelligence to Improve the Efficiency of the Market Valuation Method
DOI:
https://doi.org/10.37075/FABA.2024.2.10Keywords:
market method, artificial intelligence, finance, evaluation, efficiencyAbstract
Purpose: Advances in technology inevitably come with new potential methods for performing already established activities. Artificial intelligence, in turn, is one of the most talked-about technological innovations. Its impact on the financial sphere is still being analyzed and explored. This article examines the effect of these tools on the established market valuation methodology. The purpose of this paper is to show how digitalization and improvements in the usage of new digital technologies could prove to be useful in increasing the efficiency of already established processes such as the selected methodology for enterprise valuation: The Market approach. More specifically it focuses on artificial intelligence as a tool which can be used to improve said efficiency.
Design/Methodology/Approach: The research method used in this paper is a case study, based on a practical execution of the chosen valuation method in three different scenarios, which differ depending on the usage of AI technologies. All of the executions of the methodology are timed using a stopwatch. A subsequent comparison of results is carried out, based on the findings, and the three executions are analyzed based on speed, accuracy of results, relevancy of results and relevancy of peers.
Findings: The analysis displayed a concrete result, in which the AI used, although proving to be extremely useful in shortening the execution time of the chosen valuation method, the accuracy of the results provided by it remained very far from the truth, as is the relevance of the peers provided by the Artificial intelligence. This shows that the usage of AI could be an integral part of financial analysis in the future and could significantly improve the efficiency of the market valuation method. However, at this point in time, it should be used as a tool to facilitate analysis but not to replace it altogether.
Practical Implications: In practice, this would be able to help execute valuations significantly faster and easier than ever before, but with the necessity of the valuator to make sure the peers provided are relevant to the company being valuated.
Originality/Value: No similar study has been done regarding the implications of AI in enterprise valuation methodologies and therefore this would bring significant added value to this area of study.
Paper Type: Case study
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