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Title
Eazy Asigurari Builds an ML-Driven Insurance Pricing Engine on Amazon SageMaker AI
…arn how insurance company Eazy Asigurari is modernizing its pricing approach by building an ML-driven pricing engine on AWS. Benefits months to create a proof of concept 2 reduction in data analysis time…
Description
Romanian cloud-native insurer Eazy Asigurari built a proof of concept for a data-driven pricing engine using Amazon SageMaker AI, AWS Glue, Amazon API Gateway, Amazon RDS for PostgreSQL and Amazon DynamoDB. The ML models backtest premiums and highlight potential deviations across thousands of customer segments, with the actuarial team reviewing all ML outputs before informing pricing decisions. The proof of concept was completed within 2 months and the insurer reduced data analysis time by up to 80 percent.
…ore efficiently. Outcome | Accelerating decision-making through faster analysis Completing a proof of concept within 2 months, the insurer is moving the solution into production. The initial benchmarks are promising: Early model validation confirms alignment…
…target. This validates that the models can enrich the company’s pricing logic. Using the new ML-driven workflow, Eazy Asigurari reduced data analysis time by up to 80 percent, accelerating decision-making. The company can test scenarios and benchmark results more consistently, refinin…
Company
Eazy Asigurari
…upporting sustainable growth in a highly regulated market. About Eazy Asigurari Founded in 2023, Eazy Asigurari is a Romanian insurance company that incorporates technology into its core operations to automate key processes…
Country
Romania
…upporting sustainable growth in a highly regulated market. About Eazy Asigurari Founded in 2023, Eazy Asigurari is a Romanian insurance company that incorporates technology into its core operations to automate key processes…
Industry
Insurance
…upporting sustainable growth in a highly regulated market. About Eazy Asigurari Founded in 2023, Eazy Asigurari is a Romanian insurance company that incorporates technology into its core operations to automate key processes…
Problem
Romania's insurance market is highly regulated, limiting flexibility in how insurers calculate premiums, while customers can compare prices online with minimal effort and even small price differences can prompt them to switch providers, particularly for mandatory products such as motor third-party liability.
…erience. Opportunity | Using AWS to build a dynamic solution for Eazy Asigurari Romania’s insurance market is highly regulated, limiting flexibility in how insurers calculate premiums. At the same time, customers can compare prices online with minimal effort. Even…
Solution
Rather than replacing its existing pricing framework, Eazy Asigurari is enhancing it with ML capabilities on AWS. AWS Glue handles data ingestion and transformation, Amazon API Gateway secures data intake workflows, Amazon RDS for PostgreSQL stores the data, and Amazon DynamoDB captures logs and model outputs to support traceability. At the core, Amazon SageMaker AI lets the team build, train and deploy ML models; Eazy Asigurari customized models that can backtest premiums and highlight potential deviations across thousands of customer segments, and its actuarial team reviews all ML outputs before informing pricing decisions.
…oana Frincu. Solution | Building an ML-based, scalable pricing engine using AWS Rather than replacing its existing pricing framework, the company is enhancing it with ML capabilities. AWS Glue —a serverless service that makes data integration simpler, faster, and…
…port traceability, which is an important consideration in a regulated industry. At the core of the solution is Amazon SageMaker AI , which lets data scientists and developers build, train, and deploy ML models for virtually any use case. To efficiently validate assumptions and test pricing behavior across thousands…
Business value
Eazy Asigurari completed its proof of concept within 2 months and is moving the solution into production. Using the new ML-driven workflow, it reduced data analysis time by up to 80 percent, accelerating decision-making and allowing the company to test scenarios and benchmark results more consistently.
…i reduced data analysis time by up to 80 percent, accelerating decision-making. The company can test scenarios and benchmark results more consistently, refining pricing strategies faster and more confidently. By helping ensure premiums are competitive, Eazy Asigurari is increasing custom…
…ore efficiently. Outcome | Accelerating decision-making through faster analysis Completing a proof of concept within 2 months, the insurer is moving the solution into production. The initial benchmarks are promising: Early model validation confirms alignment…
AI capabilities
Predictive Analytics
…and test pricing behavior across thousands of customer segments, Eazy Asigurari customized models that can backtest premiums and highlight potential deviations. Then, the company’s actuarial team reviews all ML outputs before informing pri…
Technology
AWS Glue, Amazon API Gateway, Amazon RDS for PostgreSQL, Amazon DynamoDB, Amazon SageMaker AI
…port traceability, which is an important consideration in a regulated industry. At the core of the solution is Amazon SageMaker AI , which lets data scientists and developers build, train, and deploy ML models…
…per—handles data ingestion and transformation. To secure data intake workflows, Eazy Asigurari uses Amazon API Gateway —a fully managed service that makes it easy for developers to create, publish,…
Headline outcome
…odels can enrich the company’s pricing logic. Using the new ML-driven workflow, Eazy Asigurari reduced data analysis time by up to 80 percent, accelerating decision-making. The company can test scenarios and benchmark results more consistently, refinin…
Use case type
Decision support
…zed models that can backtest premiums and highlight potential deviations. Then, the company’s actuarial team reviews all ML outputs before informing pricing decisions. “Advanced pricing models require a large volume and variety of data, exceeding…
