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All Journal International Journal of New Media Technology Jurnal Indonesia Sosial Teknologi
Solontio, Chris
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Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Data Quality Issues : Case Study of Claim and Insured in Indonesia Insurance Company Solontio, Chris; Hidayanto, Achmad Nizar
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3755

Abstract

Data has become an asset for insurance companies that have many benefits and management needs to realize the importance of data quality 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 data dimensions, namely, accuracy, completeness and consistency of the relationship between claim data and insured, and findings from each data fields in this case study. In addition, researchers conducted interviews to find out the obstacles faced by IT, Customer Retention, Operational, and Actuary teams where they are directly related to data flow and data processing. From the results of the analysis, there is invalid data that will affect the analysis and cause obstacles faced by users according to the interview results. In the conclusion, management needs to form a data govenance team to avoid poor data quality that has responsibility for data flow and maintains data quality in order to provide a positive impact such as providing the right data accuracy in data analysis and user time to be more effective in data processing, assisting in making data warehouses, applying AI and digital transformation as a form of improvement in the services provided.
Data Quality Issues : Case Study of Claim and Insured in Indonesia Insurance Company Solontio, Chris; Hidayanto, Achmad Nizar
IJNMT (International Journal of New Media Technology) Vol 11 No 2 (2024): Vol 11 No 2 (2024): IJNMT (International Journal of New Media Technology)
Publisher : Universitas Multimedia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31937/ijnmt.v11i2.3755

Abstract

Data has become an asset for insurance companies that have many benefits and management needs to realize the importance of data quality 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 data dimensions, namely, accuracy, completeness and consistency of the relationship between claim data and insured, and findings from each data fields in this case study. In addition, researchers conducted interviews to find out the obstacles faced by IT, Customer Retention, Operational, and Actuary teams where they are directly related to data flow and data processing. From the results of the analysis, there is invalid data that will affect the analysis and cause obstacles faced by users according to the interview results. In the conclusion, management needs to form a data govenance team to avoid poor data quality that has responsibility for data flow and maintains data quality in order to provide a positive impact such as providing the right data accuracy in data analysis and user time to be more effective in data processing, assisting in making data warehouses, applying AI and digital transformation as a form of improvement in the services provided.
Case Study of Claim Data and Participant Data in Indonesian Insurance Companies Solontio, Chris; Hidayanto, Achmad Nizar
Jurnal Indonesia Sosial Teknologi Vol. 5 No. 12 (2024): Jurnal Indonesia Sosial Teknologi
Publisher : Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59141/jist.v5i12.7043

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.
Co-Authors Achmad Nizar Hidayanto