Selecting an Appropriate Algorithm for Risk Identification in Business Processes: Case Study Insurance Company
Keywords:
Process Mining, Risk Identification, Heuristic Algorithm, Business Processes
Abstract
Threating nature of risk for business processes causes organization manager does risk management on business processes for improve organizational performance. Process discovery algorithms typically aim at discovering process models from event logs that best describe the recorded behavior. This paper used process mining techniques for risk management of business processes. Cross-sectional method was applied in the present study through census. The population included the data extracted from Dey Co. In this study XESame12 and Prom 6.2 has been used for modeling and Alpha, Heuristic and Genetic algorithms were executed. Heuristic algorithm has maximum overall on quality dimension and it selects as the best model. Mining the business process causes corporation managers find failure processes rapidly and try to reverse engineering or improve them. This causes the agility and market share of corporation increasesReferences
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[29] M. Ashoori and M. J. Tarokh, "Applying the Process Mining Project Methodology for Insurance Risks Reduction," Int. J. of Research in Industrial Engineering, vol. 3, no. 4, pp. 57-69, 2014.
[2] H. Fehr-Duda, A. Bruhin, T. Epper and R. Schubert, "Rationality on the rise: Why relative risk aversion increases with stake size," Journal of Risk Uncertain, vol. 40, pp. 147-180, 2010.
[3] B. Ray, C. Apte, K. McAuliffl and L. Deleris, "Harnessing Uncertainty: The Future of Risk Analytics," IBM research report, 2008.
[4] C. M. G. Gusmão, "ISO, CMMI and PMBOK Risk Management: a Comparative Analysis," The International Journal of Applied Management and Technology, vol. 1, no. 1, pp. 65-75, 2003.
[5] G. K. Shaw, "A risk management model for the tourism industry in South Africa," The Potchefstroom Campus of the North-West University, 2010.
[6] M. Fischbacher and D. Smith, "The changing nature of risk and risk management: The challenge of borders, uncertainty and resilience," Risk Management Journal, vol. 11, no. 1, pp. 1-12, 2009.
[7] G. Y. Zhao, G. Zhao, C. Lv and Y. F. Sun, "Risk Management Technology for Missile Operational Support," in International Conference on Management of Innovation and Technology, 2010.
[8] L. A. Karadsheh, "A framework for integrating knowledge management with risk management for information technology projects," Lawrence Technological University, College of Management, 2010.
[9] A. A. R. El Sheikh and M. Alnoukari, Business Intelligence and Agile Methodologies for Knowledge-Based Organizations:Cross-Disciplinary Applications, 1th ed., IGI Global, 2011.
[10] V. D. Heijden, "Process Mining Project Methodology: Developing a General Approach to Apply Process Mining in Practice," TUE.School of Industrial Engineering, 2012.
[11] S. Mei-hong, J. Shou-shan, G. Yong-gang, C. Liang and C. Kai-duan, "A Method of Adaptive Process Mining Based on Time-Varying sliding Window and Relation of Adjacent Event Dependency," in International Conference on Intelligent System Design and Engineering Application, 24-31, 2012.
[12] W. V. D. Aalst, "Process Mining: Making Knowledge Discovery Process Centric," SIGKDD Explorations Journal, vol. 13, no. 20, pp. 25-49, 2011.
[13] M. Werner, N. Gehrke and M. Nüttgens, "Business Process Mining and Reconstruction for Financial Audits," in 45th Hawaii International Conference on System Science, 2012.
[14] W. V. D. Aalst and S. Dustdar, "Process Mining Put into Context," Internet Computing Journals, vol. 16, no. 1, pp. 82-86, 2012.
[15] J. C. A. M. Buijs, "Mapping Data Sources to XES in a Generic Way," Department of Mathematics and Computer Science, Eindhoven University of Technology, 2010.
[16] W. V. D. Aalst, Process Mining Discovery, Conformance and Enhancement of Business Processes, 1th ed., Springer, 2011.
[17] A. Rozinat, A. K. Alves de Medeiros, C. W. G¨unther, A. J. M. M. Weijters and W. V. D. Aalst, "The Need for a Process Mining Evaluation Framework in Research and Practice: Position Paper," in Proceeding of the 2007 international conference on Business process management, 2007.
[18] H. M. W. Verbeek, J. C. A. M. Buijs, B. F. V. Dongen and W. V. D. Aalst, "ProM6 : The Process Mining Toolkit," in Proceedings of the Business Process Management 2010 Demonstration Track, 2010.
[19] G. Lakshmanan and R. Khalaf, "Leveraging Process Mining Techniques to Analyze Semi-Structured Processes," IT Professional Journal, vol. 15, no. 5, pp. 22-30, 2012.
[20] Y. Liu, H. Zhang, C. Li and R. J. Jiao, "Workflow simulation for operational decision support using event graph through process mining," Decision Support Systems Journal, vol. 52, no. 3, pp. 685-697, 2012.
[21] J. Li, J. Ouyang and M. Feng, "A Heuristic Genetic Process Mining Algorithm," in Seventh International Conference on Computational Intelligence and Security, 2011.
[22] J. C. A. M. Buijs, B. F. Dongen and W. V. D. Aalst, "On the Role of Fitness, Precision, Generalization and Simplicity in Process Discovery," in On the Move to Meaningful Internet Systems, vol. 23, Springer, 2012, pp. 305-322.
[23] J. C. A. M. Buijs, B. F. Dongen and W. V. D. Aalst, "QUALITY DIMENSIONS IN PROCESS DISCOVERY: THE IMPORTANCE OF FITNESS, PRECISION, GENERALIZATION AND SIMPLICITY," International Journal of Cooperative Information Systems, vol. 1, p. 23, 2014.
[24] W. V. D. Aalst, H. A. Reijers, A. J. M. M. Weijters, B. F. Dongen, A. K. Alves de Medeiros, M. Song and H. M. W. Verbeek, "Business process mining: An industrial application," Information Systems Journal, vol. 33, no. 5, pp. 713-732, 2007.
[25] F. Caron, J. Vanthienen and B. Baesens, "Comprehensive Rule-Based Compliance Checking and Risk Management with Process Mining," Decision Support Systems Journal, vol. 54, no. 3, pp. 1357-1369, 2013.
[26] M. Jans, J. M. V. D. Werf, N. Lybaert and K. Vanhoof, "A business process mining application for internal transaction fraud mitigation," Expert Systems with Applications Journal, vol. 38, no. 10, pp. 13351-13359, 2011.
[27] M. Jans, N. Lybaert, K. Vanhoof and J. M. V. D. Werf, "Business Process Mining for Internal Fraud Risk Reduction: Results of a Case Study," in International Research Symposium on Accounting Information Systems, 2010.
[28] W. S. Yang and S. Y. Hwang, "A process-mining framework for the detection of healthcare fraud and abuse," Expert Systems with ApplicationsJournal, vol. 31, no. 1, pp. 56-68, 2006.
[29] M. Ashoori and M. J. Tarokh, "Applying the Process Mining Project Methodology for Insurance Risks Reduction," Int. J. of Research in Industrial Engineering, vol. 3, no. 4, pp. 57-69, 2014.
Published
2017-01-30
How to Cite
Ashoori, M. (2017). Selecting an Appropriate Algorithm for Risk Identification in Business Processes: Case Study Insurance Company. Majlesi Journal of Mechatronic Systems, 5(4). Retrieved from https://ms.majlesi.info/index.php/ms/article/view/300
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Articles
