Artificial Intelligence Based Commercial Risk Management Framework for SMEs

Gerda Žigienė, Egidijus Rybakovas and Robertas Alzbutas
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Gerda Žigienė: School of Economics and Business, Kaunas University of Technology, Gedimino str. 50, LT-44239 Kaunas, Lithuania
Egidijus Rybakovas: School of Economics and Business, Kaunas University of Technology, Gedimino str. 50, LT-44239 Kaunas, Lithuania
Robertas Alzbutas: Faculty of Mathematics and Natural Sciences, Kaunas University of Technology, Studentų str. 50–218, LT-44239 Kaunas, Lithuania

Sustainability, 2019, vol. 11, issue 16, 1-23

Abstract: Risk management in commercial processes is among the most important procedures affecting the competitiveness of small and medium-sized enterprises (SMEs), their innovativeness and potential contribution to global sustainable development goals (SDGs). The ecosystem of commercial processes is the prerequisite to manage risk faced by SMEs. Commercial risk assessment and management using elements of artificial intelligence, big data, and machine learning technologies could be developed and maintained as external services for a group of SMEs allowing to share costs and benefits. This paper aims to provide a conceptual framework of commercial risk assessment and management solution based on elements of artificial intelligence. This conceptualization is done on the background of scientific literature, policy documents, and risk management standards. Main building blocks of the framework in terms of commercial risk categories, data sources and workflow phases are presented in the article. Business companies, state policy, and academic research focused recommendations on the further development of the framework and its implementation are elaborated.

Keywords: SMEs; commercial risk; SDG; artificial intelligence; risk management framework (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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