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A publicação pode ser exportada nos seguintes formatos: referência da APA (American Psychological Association), referência do IEEE (Institute of Electrical and Electronics Engineers), BibTeX e RIS.

Exportar Referência (APA) 
Carvalho, M. C., Gonçalves, R., Lopes da Costa, R., Pereira, L. & Dias, Á. (2022). Contributions of artificial intelligence in operational risk management. International Journal of Intelligent Information Technologies. 18 (1)
Exportar Referência (IEEE) 
M. C. Carvalho et al.,  "Contributions of artificial intelligence in operational risk management", in Int. Journal of Intelligent Information Technologies, vol. 18, no. 1, 2022
Exportar BibTeX 
@article{carvalho2022_1732203453538,
	author = "Carvalho, M. C. and Gonçalves, R. and Lopes da Costa, R. and Pereira, L. and Dias, Á.",
	title = "Contributions of artificial intelligence in operational risk management",
	journal = "International Journal of Intelligent Information Technologies",
	year = "2022",
	volume = "18",
	number = "1",
	doi = "10.4018/IJIIT.296237",
	url = "https://www.igi-global.com/gateway/article/296237"
}
Exportar RIS 
TY  - JOUR
TI  - Contributions of artificial intelligence in operational risk management
T2  - International Journal of Intelligent Information Technologies
VL  - 18
IS  - 1
AU  - Carvalho, M. C.
AU  - Gonçalves, R.
AU  - Lopes da Costa, R.
AU  - Pereira, L.
AU  - Dias, Á.
PY  - 2022
SN  - 1548-3657
DO  - 10.4018/IJIIT.296237
UR  - https://www.igi-global.com/gateway/article/296237
AB  - Considering the last decades and several economic crises, Operational Risk is a rising area and companies are slowly realizing that the more they invest on it, the less profits they lose. Artificial Intelligence is the critical topic of the century, wide enough to cover all conceivable areas, bringing easy, cheaper, and more precise ways of doing tasks. This paper reflects the progresses of implementing Artificial Intelligence technologies in the control of Operational Risks. The qualitative research revealed the deficiency of investment, as well as the absence of information concerning the progresses on the AI technologies applicable to OpRisk controls. Obstacles as the lack of human resources capabilities and prioritising other sectors are impediments to this automation. Companies must invest in the OpRisk departments, considering the existing AI solutions that allow the maturation of OpRisk controls and, therefore, to mitigate losses that occur from them.
ER  -