Application of Process Mining with Fuzzy Models to Loan Processing

Abstract

Process mining is used extensively in recent years to develop the steps of the business. Also, process mining is an important technique to remove waste and reduce process costs. The aims of this study indicate that congestion, workflow which lived a long time, and stuff or system statistics in the banking real estate transaction process. In this work, the process mining practice is applied in bank business loans. In the bank process, the most used and more complicated business is a bank loan transaction. The process mining implementation pattern is created with sample and flow gains of process development. Then, the new workflow designed and the pattern is executed. In this study, in the first stage of the total loan period, 7.84 hours of earnings are obtained. Visualizations of the process have been affected with the help of fuzzy model algorithms necessary to the huge number of incidents and activities. Workflow analysis and gather information for studies were set up to be effortless with the support of fuzzy models. As a result of the analysis based on the flows, the knowledge pool is created by getting the knowhows such as the average duration of the process and the deviations in the users or systems. The results indicated that process mining is a significant methodology for developing bank loan transactions and enhancement their performance.