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Review Article Open Access December 24, 2022

Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers

Avinash Reddy Aitha 1,*
1
Software Engineer, US Bank, Minneapolis, MN 55402, United States
Publihed in: Current Research in Public Health (Volume 2, Issue 1, 2022)
Page(s): 50-63
DOI: 10.31586/ujbm.2022.1347
Received
July 16, 2022
Revised
September 23, 2022
Accepted
October 28, 2022
Published
December 24, 2022
Keywords
Cloud Native; ETL; Real-Time Processing; Claims Processing
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2022. Published by Scientific Publications
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Cite This Article

APA Style
Aitha, A. R. (2022). Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers. Current Research in Public Health, 2(1), 50-63. https://doi.org/10.31586/ujbm.2022.1347
ACS Style
Aitha, A. R. Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers. Current Research in Public Health 2022 2(1), 50-63. https://doi.org/10.31586/ujbm.2022.1347
Chicago/Turabian Style
Aitha, Avinash Reddy. 2022. "Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers". Current Research in Public Health 2, no. 1: 50-63. https://doi.org/10.31586/ujbm.2022.1347
AMA Style
Aitha AR. Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers. Current Research in Public Health. 2022; 2(1):50-63. https://doi.org/10.31586/ujbm.2022.1347 
@Article{crph1347,
AUTHOR = {Aitha, Avinash Reddy},
TITLE = {Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers},
JOURNAL = {Current Research in Public Health},
VOLUME = {2},
YEAR = {2022},
NUMBER = {1},
PAGES = {50-63},
URL = {https://www.scipublications.com/journal/index.php/UJBM/article/view/1347},
ISSN = {2831-5162},
DOI = {10.31586/ujbm.2022.1347},
ABSTRACT = {Cloud native ETL pipelines support the extract and transform phases of real time claims processing in large scale insurers. The cloud native approach offers dramatic improvements in scalability, reliability, resiliency and agility as well as seamless integration with the diverse set of data sources, destinations and technologies characteristic of large scale insurers. The ETL process extracts data from source systems such as core transaction, fraud, customer and accounting processes, transforms the data to create a usable format for analytics and other applications, and loads the resulting tables into business intelligence or data lake systems for subsequent storage and analysis. By addressing these two phases of the overall ETL process, cloud native ETL pipelines can provide timely, reliable and consistent data to data scientists, actuaries, underwriters and other analysts. Real time processing represents a key priority within the overall claims process: faster, more accurate claim approvals reduce insurer costs, improve customer service and enhance premium pricing. As a result, a variety of claims related use cases are moving from batch to real time.},
}
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AB  - Cloud native ETL pipelines support the extract and transform phases of real time claims processing in large scale insurers. The cloud native approach offers dramatic improvements in scalability, reliability, resiliency and agility as well as seamless integration with the diverse set of data sources, destinations and technologies characteristic of large scale insurers. The ETL process extracts data from source systems such as core transaction, fraud, customer and accounting processes, transforms the data to create a usable format for analytics and other applications, and loads the resulting tables into business intelligence or data lake systems for subsequent storage and analysis. By addressing these two phases of the overall ETL process, cloud native ETL pipelines can provide timely, reliable and consistent data to data scientists, actuaries, underwriters and other analysts. Real time processing represents a key priority within the overall claims process: faster, more accurate claim approvals reduce insurer costs, improve customer service and enhance premium pricing. As a result, a variety of claims related use cases are moving from batch to real time.
DO  - Cloud Native ETL Pipelines for Real Time Claims Processing in Large Scale Insurers
TI  - 10.31586/ujbm.2022.1347
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