Modern Event-Driven Insurance Claims Processing with AWS AI
An anonymous insurance customer built a scalable, fault-tolerant claims processing system with fraud detection using AWS services. The solution includes event-driven architecture with serverless AWS Step Functions, Amazon SQS, Amazon API Gateway, Amazon S3, Amazon Rekognition, Amazon Textract AnalyzeID API, AWS Lambda, Amazon DynamoDB, and AWS IoT Core. The architecture orchestrates customer onboarding, document processing for driver licenses and car images, claims handling, and automated fraud detection by analyzing identity documents and images. EventBridge and Step Functions manage asynchronous event workflows, enabling extensible, modular design allowing faster feature releases and third-party integration. Fraud detection compares extracted identity info with onboarding data and triggers fraud alerts if mismatches detected. The system uses Amazon SQS queues to handle event spikes and Lambda functions for processing claims and notifications. Bi-directional integration with third-party systems like Salesforce enables combined AI/ML fraud and sentiment analysis for enriched customer experience.
- Organization
- Anonymous insurance customer
- Industry
- Insurance
- Location
- United States
- Published
- March 2023
Reported outcomes
Strategic outcomes
Primary read
Use case focus
Showing 2 of 2
- 1Claims Processing Automation
- 2Fraud Detection
- The customer needed a modern, scalable, and fault-tolerant solution to process insurance claims efficiently.
- They aimed to automate fraud detection in document uploads to reduce manual effort and improve accuracy.
- The architecture had to be extensible and modular to allow faster feature releases and integration with third-party services
- Used AWS serverless services in an event-driven architecture to build claims processing with customer onboarding, document processing, claims handling, and fraud detection workflows.
- Leveraged AWS Step Functions for orchestrating state machines and workflows per business domain, integrating with Amazon EventBridge as event broker.
- Implemented document processing workflows using Amazon Rekognition to classify documents and Amazon Textract AnalyzeID API to extract identity info from driver licenses.
- Employed Amazon S3 event notifications and EventBridge rules to trigger document processing and fraud detection asynchronously.
- Used Lambda functions for claims processing and notifications, Amazon SQS to buffer spikes, and AWS IoT Core for real-time customer notifications.
- Integrated with Salesforce CRM via EventBridge for real-time AI-enhanced customer service including sentiment and fraud analyses.
- Improved scalability and fault tolerance of insurance claims processing.
- Automated fraud detection by validating identity documents reduces manual review.
- Extensible architecture facilitates faster feature releases and smoother third-party integrations.
- Enhanced customer experience through real-time notifications and AI-powered CRM integration.
- Reduced operational risk by isolating domain faults and enabling graceful degradation.
Architecture
The architecture is an event-driven, serverless application on AWS using Step Functions, EventBridge as an event broker, Lambda, Amazon Rekognition, Amazon Textract AnalyzeID API, S3, DynamoDB, and SQS. It handles customer onboarding, document uploads, claims filing, fraud detection, and notifications through asynchronous event workflows and state machines.
Sources & evidence1
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