Data Science and Analytics for Decision Support (SIG DSA)
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Paper Type
Complete
Paper Number
1278
Description
Artificial Intelligence (AI) is becoming more popular in a wide variety of application areas in finance. It is expected that human tasks in analyzing data can be replaced by the use of AI while saving time and costs. AI-based methods can be used to support several decision problems in the context of financial statement analysis. This paper describes the iterative development process towards a taxonomy of AI-based methods in the financial statement analysis. The purpose of the taxonomy is to create a classification pattern that can serve practitioners and researchers as a foundation for future development and measurement of different methods. Therefore, we examined criteria for developing AI-based methods, while referring to the identified major use-cases in financial statement analysis within academic literature as well as practice publications. We identified six dimensions and fifteen corresponding characteristics that refer to the developing process of AI-based methods in financial statement analysis.
Recommended Citation
Nießner, Tobias; Nickerson, Robert C.; and Schumann, Matthias, "Towards a taxonomy of AI-based methods in Financial Statement Analysis" (2021). AMCIS 2021 Proceedings. 6.
https://aisel.aisnet.org/amcis2021/data_science_decision_support/data_science_decision_support/6
Towards a taxonomy of AI-based methods in Financial Statement Analysis
Artificial Intelligence (AI) is becoming more popular in a wide variety of application areas in finance. It is expected that human tasks in analyzing data can be replaced by the use of AI while saving time and costs. AI-based methods can be used to support several decision problems in the context of financial statement analysis. This paper describes the iterative development process towards a taxonomy of AI-based methods in the financial statement analysis. The purpose of the taxonomy is to create a classification pattern that can serve practitioners and researchers as a foundation for future development and measurement of different methods. Therefore, we examined criteria for developing AI-based methods, while referring to the identified major use-cases in financial statement analysis within academic literature as well as practice publications. We identified six dimensions and fifteen corresponding characteristics that refer to the developing process of AI-based methods in financial statement analysis.
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