Using big data analytics in risk management, risk assessment and risk evaluation. The case of employee attrition

Abstract

The scope of this master dissertation is to evaluate and analyze the concept and use of big data analytics in risk management, risk assessment and risk evaluation. The main risk frameworks are considered and presented. Also, the formal notion of big data is disclosed. Ways big data can be used to assist risk management process in organizations in various levels like operation level or even strategic level will be surveyed. To sustain theoretical analysis an open-source dataset is used to present the case of employee attrition. It is indispensable for contemporary organizations to retain their most valuable asset, employees. However nowadays, the negative phenomenon of employee attrition has reached an alarming level. As presented in the case study, Big Data analytics can assist in identifying and evaluating risk factors that ‘‘feed’’ employee attrition. Furthermore, machine learning algorithms are developed that could guide organizations in proactively recognizing individuals with high probability of attrition so that mitigation measures could be deployed in time.