Mining Process Evaluation in Discovering the Semi-Automatic Processes of the Banking Industry (the case: Bank guarantee issuance process)

Nowadays the process performance is a key success factor in the competitive environment of banking industry. Various approaches have been proposed to identify and improve processes. Process mining is a new process management approach which is supposed to discover and improve the actual process model based on information technology. Despite of the theoretical development, authors have paid less attention to process mining applicability. In this paper applicability of the Fuzzy Miner algorithm of process mining to semi-automatic processes is investigated. We used PM2 methodology with some changes at the first and the fifth step to discover a semi-automated process model. At the first step manual and system data is combined and the desired detail level is determined by process owners. Then the model is discovered by means of Fuzzy Miner algorithm through ProM tool. As the manual data could affect the discovered model adversely so besides conformance checking criteria a new expert based criteria is proposed to validate the model. The expert validation criteria is equal to 87.2 percent for the discovered model of the selected process which means process mining could be applied to semi-automated processes successfully