How Generative AI transformed claims processing for an Insurtech leader

The insurtech industry is undergoing rapid transformation, driven by the demand for faster, more accurate, and customer-centric solutions. One of the leading trends in this sector is the integration of Generative AI to streamline complex processes such as claims verification and policy management.

In this case study, you’re going to explore how we helped our customer develop an AI-enabled platform that revolutionized the insurance process for electronic devices.

Customer overview

Our customer is a global financial services company specializing in insurtech solutions for electronic devices. Focused on enhancing insurance processes through technology, they offer innovative and scalable products to streamline claims and policy management across diverse markets.

Customer challenges

Their existing infrastructure for managing insurance policies and claims, particularly in the electronic devices sector, was proving inadequate. To stay competitive and maintain their global reach, they needed a robust, scalable platform to automate processes, improve the customer experience, and seamlessly integrate stakeholders.

1. Manual claims processing: Their system required extensive manual intervention, causing delays and customer dissatisfaction.

2. Lack of predictive capabilities: There was no check in place to proactively identify potential claims issues or detect fraudulent activities at an early stage. This lack of foresight led to slower decision-making, higher operational costs, and reduced efficiency in claims processing.

3. Fragmented user experience: The insurance process for policy acquisition and claims filing was cumbersome, making it difficult for customers to navigate.

4. Integration issues: Connecting insurers, distributors, and customers into a cohesive ecosystem was difficult, limiting their ability to innovate and scale efficiently.

The partnership between Applify and other AWS Partners

Our customer was working closely with multiple AWS partners, each bringing niche expertise to the table to engineer the entire product. Recognizing the need for a strategic approach, they collaborated with us to kickstart the project with a small-scale Proof of Concept (PoC), focusing on AI capabilities for claims processing. 

This initial PoC allowed us to demonstrate the viability of Generative AI in automating claims verification and predicting claims outcomes. Upon successful completion, we scaled the solution, transforming it into a comprehensive platform that optimized claims processing, integrated seamlessly with their existing systems, and enhanced overall operational efficiency across the board.

Our expertise with Generative AI

With deep knowledge of AWS, its services, and technologies, we provided strategic guidance and technical expertise to our customers.

• Predictive analytics: Built predictive analytics models using Amazon SageMaker, allowing the customer to forecast claims outcomes, detect fraudulent claims, and proactively manage claims processing.
• Scalable infrastructure on AWS: Designed a scalable architecture using Amazon EC2, Amazon ECS, and AWS Lambda, allowing the platform to handle increasing data volumes as the business grew.
• Real-time data processing: We enabled real-time data processing for claims submissions, ensuring that large amounts of claims data could be processed instantly, providing actionable insights.
• Secure data management: Implemented robust security measures to ensure the platform adhered to the highest security standards, protecting sensitive customer data and ensuring compliance with regulatory requirements.

The AWS infrastructure powering the solution

We leveraged a comprehensive suite of AWS services that provided the foundation for automation, real-time data processing, and global scalability.

1. Amazon SageMaker: Used to build, train, and deploy machine learning models for claims verification and predictive analytics. This powered the Generative AI models that automated damage assessment and claim approvals.

2. Amazon Rekognition: Enabled image analysis by automatically assessing damage to electronic devices using customer-provided images. This reduced the need for manual inspection and improved the accuracy of claims assessments.

3. Amazon Textract: Leveraged to automatically extract data from scanned documents, such as receipts and invoices. This automated the document review process, accelerating claims submissions and approvals.

4. Amazon Kinesis: Used for real-time data streaming to handle claims data as it was submitted. Kinesis allowed the system to instantly process large volumes of incoming claims data and generate insights for further action.

Success metrics

The enhancement of the existing infrastructure and the implementation of Generative AI into the customer’s insurtech platform delivered transformative results across several key areas.

• 50% Faster in claims processing time: Automation of claims verification enabled faster assessments and approvals, reducing the average processing time by half.
• 45% Increase in accuracy of damage assessment: AI models trained on historical claims data, enabled the platform to achieve higher accuracy, from 20% to 65%, in assessing damages to electronic devices, and minimized errors in claims processing.
• ‍40% Reduction in operational costs: Predictive analytics, powered by Generative AI, reduced the need for manual intervention, leading to a 40% decrease in operational costs related to claims processing.