{"slug":"building-a-central-data-analytics-and-ai-solution-using-aws-with-generali","url":"https://findausecase.com/use-cases/building-a-central-data-analytics-and-ai-solution-using-aws-with-generali","title":"Building a central data, analytics, and AI solution using AWS with Generali","description":"Insurance and asset management group Generali built a central data, analytics and AI solution on AWS to standardize AI adoption across its more than 40 operating entities, using Amazon Redshift for the central data warehouse, AWS Glue for data-quality and transformation pipelines, Amazon SageMaker AI to automate claim settlement and predictive payout modeling, and Amazon Bedrock to power a generative AI customer-assistance agent providing instant responses. The company developed 16 flagship AI use cases spanning pricing, underwriting, claims processing and operations, deployable across operating entities via a centralized Global AI engine, while complying with GDPR and internal governance policies.","company":"Generali","industry":"Insurance","aiCapabilities":["Generative AI","Machine Learning","Predictive Analytics"],"technology":["Amazon Bedrock","Amazon SageMaker AI","Amazon Redshift","AWS Glue"],"deployment":"Public Cloud","problemStatement":"Generali wanted to explore the use of AI and automation to improve cost efficiency, technical results, and the customer experience, needing to consolidate a common data view and develop and deploy common AI applications across its more than 40 operating entities without duplicating efforts, while complying with regulations such as GDPR.","solutionApproach":"Generali built a central data and analytics solution on Amazon Redshift, ingesting text, images and structured data from operating entities and external sources like weather data and satellite images, and using AWS Glue for data-quality and transformation pipelines. Generali uses Amazon SageMaker AI to automate claim settlements and predictive modeling to propose appropriate payouts in injury claim negotiations. It developed 16 flagship AI use cases across pricing, underwriting, claim processing and operations, deployable across operating entities via a centralized Global AI engine. Using Amazon Bedrock, Generali also built a generative AI customer-assistance agent providing automated, instant responses to assistance requests.","businessValue":"In the first three years of implementing its flagship use cases, Generali saved more than EUR €200 million in operating costs, accelerated its customer response time by automatically processing more than 21 million API calls per month, and decreased claim settlement time from several days to 1 day or, for simple health claims, to seconds. Generali increased the number of its AI applications from 5 to over 50 in 3 years, with a goal of 200 applications in the next 3 years.","evidence":{"band":"high"},"sourceUrl":"https://aws.amazon.com/solutions/case-studies/generali/","dates":{"publishedAt":"2026-08-19T07:59:09.395Z","publishedAtSource":"pipeline","updatedAt":"2026-08-19T07:59:09.395Z"},"license":"Open for reading and citing with a link to https://findausecase.com/use-cases/building-a-central-data-analytics-and-ai-solution-using-aws-with-generali. Bulk republication requires permission."}