Case Study of Claim Data and Participant Data in Indonesian Insurance Companies

Abstract

Data has become an asset for insurance companies that has many benefits, especially health insurance, so that management needs to realize the importance of good data quality in order to avoid the impact of poor data quality. In this study, data quality measurement will be carried out by observation to see the total amount of invalid data from the data dimensions, namely, accuracy, completeness and consistency of the relationship between claim data and customer data as well as the findings of the overall data of each case study site. In addition to the data analysis, interviews were conducted with the IT, Customer Retention, Operations, and Actuarial teams who are directly related to data flow and data processing to create an analysis that helps management in making decisions. From the results of the analysis and interviews that have been conducted, there are still data that do not match and obstacles faced by users in dealing with poor data quality. From the results of this analysis, management needs to form a data govenance team that has the responsibility of the entire data flow and maintaining data quality. Later, the managed data set will have a positive impact on other teams in terms of analyzing trends or fraud in a faster time, assisting in the creation of a data warehouse, implementing artificial intelligence (AI) and digital transformation as a form of company improvement to insurance policyholders.