Prediction of Process Failure Approach Using Process Mining

Abstract

Events log are a collection of events that concern a business process. In them, we may find cases where its output is different from what expected. These differences are considered as failure and many publications usually propose prediction model to improve the business model. But existing approach of prediction rarely take into account the loops. The aim of this work is to propose a prediction of business process failure while considering loops as failure. So, in order to introduce the loop, we need first to determine how to implement the loop in existent event log. We propose some machine learning model in order to do the prediction. And then, compare the prediction model in order to get the best one. The prediction model is made by using the event log’s dataset of a loan application performed in a financial institution.