Is artificial intelligence ready to assess an enterprise's financial security?

Artikel

This study contributes to the literature on financial security by highlighting the relevance of the perceptions and resulting professional judgment of stakeholders. Assessing a company's financial security using only economic indicators-as suggested in the existing literature-would be inaccurate when undertaking a comprehensive study of financial security. Specifically, indices and indicators based on financial or managerial reporting calculated at any particular point in time, provide only a superficial understanding-and may even distort the overall picture. It has also been suggested that expert assessment is the most objective method, although it has disadvantages related to individual cognitive limitations. These limitations are not particular to artificial intelligence, which could assess an enterprise's financial security in a less biased way. However, by only imitating human behavior, it is not able to perceive and evaluate with intuition the dynamics of the company's development and holistically assess the financial condition-despite the possibility of learning and forecasting—because artificial intelligence is not able to think and predict, which, in an enterprise, is the most important skill of a manager. Therefore, the risk of developing artificial intelligence to assess a firm's financial security lies in a biased assessment of the enterprise's activities in general-and its financial security in particular.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: Journal of Risk and Financial Management ; ISSN: 1911-8074 ; Volume: 13 ; Year: 2020 ; Issue: 9 ; Pages: 1-19 ; Basel: MDPI

Classification and Topics

• Classification: Wirtschaft
• Subject: artificial intelligence ; cognitive biases ; cognitive limitations ; economic analysis ; financial security ; professional judgment

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Melnychenko, Oleksandr
• Event: Veröffentlichung
• (who): MDPI
• (where): Basel
• (when): 2020

Further information

• DOI: doi:10.3390/jrfm13090191
• Handle: http://hdl.handle.net/10419/239303
• Last update: 10.03.2025, 11:42 AM CET