Artificial Intelligence (AI) – simply referring to the intelligence exhibited by machines, as opposed to natural intelligence displayed by humans – is reshaping business, economy, and society. However, so far, knowledge in this field is still limited and highly fragmented, and primarily technical-oriented. In addition, the literature review demonstrates that academia has offered limited application-oriented research to support firms and managers implementing AI. This paper is based on a qualitative meta-analysis to identify the various areas of application of AI in financial risk assessment. The analysis identified Credit Risk & Credit Scoring, Forecasting & Prediction, Security, and Fraud Detection as major research areas of AI in finance. Furthermore, this paper identified how different AI applications are applied in business and demonstrated the impact of these applications. In addition, this research highlights promising AI applications for businesses and applications that are currently not suitable for implementation. Finally, promising research opportunities in AI-related business research are outlined. The description is necessary to advance the current technical-dominated research to include business-oriented research and application-specific research on artificial intelligence.
| Published in | American Journal of Management Science and Engineering (Volume 7, Issue 4) |
| DOI | 10.11648/j.ajmse.20220704.14 |
| Page(s) | 59-68 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2022. Published by Science Publishing Group |
Artificial Intelligence, AI, Finance, Systematic Literature Review, Risk Assessment
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APA Style
Ralf Wandmacher, Christian Sturm, Philipp Weber, Paul Kuhn. (2022). Artificial Intelligence in Business Management: A Literature Review on AI Applications on Risk Assessment in the Financial Industry. American Journal of Management Science and Engineering, 7(4), 59-68. https://doi.org/10.11648/j.ajmse.20220704.14
ACS Style
Ralf Wandmacher; Christian Sturm; Philipp Weber; Paul Kuhn. Artificial Intelligence in Business Management: A Literature Review on AI Applications on Risk Assessment in the Financial Industry. Am. J. Manag. Sci. Eng. 2022, 7(4), 59-68. doi: 10.11648/j.ajmse.20220704.14
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Download@article{10.11648/j.ajmse.20220704.14,
author = {Ralf Wandmacher and Christian Sturm and Philipp Weber and Paul Kuhn},
title = {Artificial Intelligence in Business Management: A Literature Review on AI Applications on Risk Assessment in the Financial Industry},
journal = {American Journal of Management Science and Engineering},
volume = {7},
number = {4},
pages = {59-68},
doi = {10.11648/j.ajmse.20220704.14},
url = {https://doi.org/10.11648/j.ajmse.20220704.14},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmse.20220704.14},
abstract = {Artificial Intelligence (AI) – simply referring to the intelligence exhibited by machines, as opposed to natural intelligence displayed by humans – is reshaping business, economy, and society. However, so far, knowledge in this field is still limited and highly fragmented, and primarily technical-oriented. In addition, the literature review demonstrates that academia has offered limited application-oriented research to support firms and managers implementing AI. This paper is based on a qualitative meta-analysis to identify the various areas of application of AI in financial risk assessment. The analysis identified Credit Risk & Credit Scoring, Forecasting & Prediction, Security, and Fraud Detection as major research areas of AI in finance. Furthermore, this paper identified how different AI applications are applied in business and demonstrated the impact of these applications. In addition, this research highlights promising AI applications for businesses and applications that are currently not suitable for implementation. Finally, promising research opportunities in AI-related business research are outlined. The description is necessary to advance the current technical-dominated research to include business-oriented research and application-specific research on artificial intelligence.},
year = {2022}
}
TY - JOUR T1 - Artificial Intelligence in Business Management: A Literature Review on AI Applications on Risk Assessment in the Financial Industry AU - Ralf Wandmacher AU - Christian Sturm AU - Philipp Weber AU - Paul Kuhn Y1 - 2022/08/24 PY - 2022 N1 - https://doi.org/10.11648/j.ajmse.20220704.14 DO - 10.11648/j.ajmse.20220704.14 T2 - American Journal of Management Science and Engineering JF - American Journal of Management Science and Engineering JO - American Journal of Management Science and Engineering SP - 59 EP - 68 PB - Science Publishing Group SN - 2575-1379 UR - https://doi.org/10.11648/j.ajmse.20220704.14 AB - Artificial Intelligence (AI) – simply referring to the intelligence exhibited by machines, as opposed to natural intelligence displayed by humans – is reshaping business, economy, and society. However, so far, knowledge in this field is still limited and highly fragmented, and primarily technical-oriented. In addition, the literature review demonstrates that academia has offered limited application-oriented research to support firms and managers implementing AI. This paper is based on a qualitative meta-analysis to identify the various areas of application of AI in financial risk assessment. The analysis identified Credit Risk & Credit Scoring, Forecasting & Prediction, Security, and Fraud Detection as major research areas of AI in finance. Furthermore, this paper identified how different AI applications are applied in business and demonstrated the impact of these applications. In addition, this research highlights promising AI applications for businesses and applications that are currently not suitable for implementation. Finally, promising research opportunities in AI-related business research are outlined. The description is necessary to advance the current technical-dominated research to include business-oriented research and application-specific research on artificial intelligence. VL - 7 IS - 4 ER -
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