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Advances In Social Humanities Research
Published by Sahabat Publikasi
ISSN : 30323037     EISSN : 30315786     DOI : doi.org/10.46799/adv.v2i2.187
Core Subject : Humanities, Social, Engineering,
Humanities Engineering Law, Crime, Criminology & Criminal Justice Social Sciences
Advances In Social Humanities Research is a double blind peer-reviewed academic journal and open access to social and humanities fields. The journal is published monthly by Sahabat Publikasi Advances In Social Humanities Research provides a means for sustained discussion of relevant issues that fall within the focus and scopes of the journal which can be examined empirically. This journal publishes research articles covering social and humanities fields. Published articles are from critical and comprehensive research, studies or scientific studies on important and current issues or reviews of scientific books. This journal publishes research articles covering social and technology.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 371 Documents
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Artificial Intelligent Architecture Analysis in Life Insurance Company Boy Bismar; Heru Purnomo Ipung; Eka Budiarto
Advances In Social Humanities Research Vol. 4 No. 3 (2026): Advances In Social Humanities Research
Publisher : Sahabat Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46799/adv.v4i3.548

Abstract

The life insurance industry faces increasing challenges due to complex processes, growing customer expectations, and competitive pressures. This research explores the transformative potential of Artificial Intelligence (AI) in revolutionizing end-to-end processes within the life insurance sector. By leveraging AI technologies such as machine learning, predictive analytics, and natural language processing, insurers can address inefficiencies in underwriting, claims processing, policy changes, and renewals—improving both speed and accuracy while ensuring regulatory compliance. The study adopts a comprehensive research methodology using TOGAF, beginning with a literature review and user interviews to identify existing challenges and inefficiencies in life insurance processes. A detailed architecture vision was developed using fishbone analysis and solution concept diagrams. Business and technology architectures were designed to address gaps, leveraging AI-driven tools to enhance risk assessment, fraud detection, and customer engagement. Expert validation was incorporated to ensure the practical applicability of the proposed solutions. The research presents an AI architecture tailored to various life insurance processes, including proposal creation, new business/underwriting, renewal, policy changes, claims management, agent commission, financial report, premium reserve, and reinsurance. Key innovations include predictive models for risk scoring, fraud detection algorithms, and churn prediction models to enhance customer retention. The study highlights the significance of AI-driven personalization, operational efficiency, and decision-making in optimizing these processes. The findings emphasize the importance of aligning AI integration with organizational goals and compliance standards. AI not only expedites processing but also enhances customer satisfaction and competitiveness in a rapidly evolving market.

Page 38 of 38 | Total Record : 371

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