Amazon EMR Serverless

Amazon EMR Serverless is a serverless option in Amazon EMR that lets data analysts and engineers run open-source big data analytics frameworks, such as Apache Spark and Apache Hive, without configuring, managing or scaling clusters or servers. It automatically provisions and scales compute and memory resources on demand, and customers pay only for what they use. It eliminates local storage provisioning for Apache Spark workloads, reducing data processing costs by up to 20% and preventing job failures from disk capacity constraints.

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Machine Learning

top AI capability

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InsuranceMachine Learning

How Mapfre Insurance modernized fraud claims with Amazon EMR Serverless

Mapfre Insurance, the number one auto and home insurer in Massachusetts, modernized fraud detection by combining graph-based features from Neo4j with machine learning models deployed on AWS, using Amazon EMR Serverless, Apache Iceberg tables on Amazon S3, AWS Glue Data Catalog, AWS Lake Formation, and Amazon MWAA for orchestration. Fraud predictions integrate directly with Guidewire Claims via AWS Lambda, automatically creating claim activities showing the top model drivers for adjusters. The initiative, covering Massachusetts Auto insurance and later expanded to Home insurance, has delivered more than $5 million in Net Present Value, with detection accuracy improved 50-135 percent compared to baseline methods.

Mapfre Insurance· United StatesAmazon EMR Serverless · Apache Iceberg · AWS Glue Data Catalog +5