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Digital Transformation Strategy for the Insurance of the Motor Branch Using Artificial Intelligence (AI)

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dc.contributor.author Presented by: LAKHZOUM, Farah
dc.contributor.author Supervisor: TABTI, Rafika
dc.date.accessioned 2025-11-04T13:57:25Z
dc.date.available 2025-11-04T13:57:25Z
dc.date.issued 2025-07-02
dc.identifier.uri http://dspace.esgen.edu.dz:8080/xmlui/handle/123456789/774
dc.description 226 p en_US
dc.description.abstract This study addresses how artificial intelligence can enhance GIG Algeria’s motor insurance operations, from subscription to claims management, while optimizing efficiency and maintaining customer trust through a balanced integration of technology and human oversight with an in-depth study of GIG Algeria. It is based on a mixed methodological approach combining quantitative and qualitative studies along with process design. The results show that stakeholders demonstrate strong support for digital transformation and AI implementation across the entire motor insurance process. Customers exhibited significant acceptance and expressed a genuine need for AI-driven solutions to improve accessibility and speed. The findings highlight the development of a strategic framework that leverages technological innovation to streamline operations while ensuring customer-centricity and creating a robust foundation for this innovative project at GIG Algeria. The study demonstrates that digital transformation in motor insurance requires careful integration of automated processes while preserving essential human touchpoints to enhance customer experience and operational efficiency. en_US
dc.language.iso en en_US
dc.publisher HIGHER SCHOOL OF MANAGEMENT AND DIGITAL ECONOMY en_US
dc.subject AI en_US
dc.subject motor insurance en_US
dc.subject subscription en_US
dc.subject claims management en_US
dc.subject automation en_US
dc.subject digital transformation en_US
dc.title Digital Transformation Strategy for the Insurance of the Motor Branch Using Artificial Intelligence (AI) en_US
dc.title.alternative Case Study: GIG Algeria en_US
dc.type Thesis en_US


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