People: Insurers need to get the right stakeholders on board, as AI initiatives often require cross-functional collaboration. This can be challenging, as many people working on AI projects in insurance companies do not have dedicated roles – they are taking on AI-related work in addition to their regular responsibilities. Finding the right stakeholders who are willing to drive these initiatives forward is an important step.

Process: Insurers must establish a framework for scoring, onboarding, and deploying new use cases, as well as driving user adoption. A well-defined process ensures a smooth transition and maximises the impact of AI-powered solutions.

Platforms: Insurers need to address security, ethics, and compliance considerations when implementing AI-powered technologies. Establishing the right guardrails and data architecture is essential for successful AI deployment on the right technology platforms.

Additionally, it’s important to note that AI is only as good as the data it is trained on. Many insurers struggle with their AI roadmap due to challenges in data strategy, data architecture, and data quality.

Intelligent document processing with Amazon Textract

By using AI-powered AWS services, such as Amazon Textract, insurers can build intelligent claims processing systems that can automatically extract and analyse relevant data from claims documents, images and other sources. This not only reduces the manual effort required, but also improves the accuracy and consistency of the claims assessment process.

Amazon Textract is a powerful document processing service that can extract text, tables and other structured data from scanned documents and images. This allows insurers to automate the extraction of claim forms and other supporting documents that reduces the time and effort required for manual data entry. By using Amazon Textract, insurers can streamline their claims processing workflows, reducing operational costs and improving overall efficiency.

Elevance Health, a major health insurance provider, implemented Amazon Textract to transform its insurance claims processing operations, and automate a wide range of insurance documents. By doing so the company were able to reduce manual data entry, improve data accuracy, and accelerate key processes like claims adjudication and reimbursement queries. This resulted in an estimated $9 million in savings over the next 5 years, demonstrating the substantial financial impact that AI-driven document processing can have for insurers looking to maximise their ROI.

Achieving zero-touch claims with integrated AI/ML solutions

The insurance industry has long envisioned to achieve the concept of zero-touch claims (ZTC), where the entire claims process can be handled with minimal or no human intervention. This goal has become increasingly attainable with the rise of AI and machine learning technologies, which can automate and streamline critical aspects of the claims journey. As already highlighted, AI-powered services like Amazon Textract can significantly improve the efficiency of claims processing, however, to truly achieve the full potential of ZTC, insurers need to integrate a combination of complementary AWS AI/ML services.

By integrating Amazon Textract with other capabilities like Amazon Rekognition for computer vision and Amazon Comprehend for natural language processing, insurers can automate the entire claims journey – from first notice of loss to settlement. This includes automatically extracting and analysing data from claims documents, assessing damage through computer vision, and using natural language processing to understand the context of each claim. According to AWS, this integrated approach to intelligent document processing can deliver up to 73% ROI for businesses, making it a strategic area of focus for achieving significant financial impact.

AWS architecture for AI-driven insurance solutions

Below is a conceptual architecture diagram showcasing how AWS services can work together in a unified solution to deliver zero-touch claims processing, optimise fraud detection, and enhance customer engagement. This architecture emphasises the flow of data through multiple layers, ensuring seamless automation, security, and actionable insights:

The workflow begins with data ingestion through Amazon S3 and AWS Glue, where raw claims documents and other inputs are prepared. The AI/ML processing layer then analyses these inputs using Amazon Textract, Amazon Rekognition, and Amazon Comprehend. AWS Lambda and AWS Step Functions orchestrate the flow, connecting to customer-facing tools like Amazon Lex and Amazon Polly for engagement, and feeding data into Amazon Athena and Amazon QuickSight for real-time analysis and reporting. This end-to-end solution provides insurers with a scalable, secure, and highly efficient system for managing claims and optimising operations.

Fraud detection and risk assessment with Amazon SageMaker

Insurers suffer substantial losses (up to 10% of premium) every year due to fraudulent claims. By leveraging Amazon SageMaker, insurers can build custom ML models to proactively detect and alert on suspicious and fraudulent policies and claims. This helps reduce operational costs and improve the overall financial performance of the business.

In addition, Amazon SageMaker can be used to develop and deploy custom machine learning models that can analyse a wide range of data sources, such as customer demographics and historical claims data, to identify patterns and predict future risk. This can help insurers to more accurately price their policies, reducing the risk of under-pricing or overpricing, and improving their profitability overall.

Zego, a motor insurance provider, uses Amazon SageMaker to build ML models that analyse real-time driver performance data, enabling automatic insurance pricing based on actual driving behaviour. This has allowed Zego to reduce compute costs by 50% and improve application performance by up to 80%, thereby offering more competitive premiums while maintaining profitability. This case study highlights how AWS can help insurers streamline their operations and pricing through data-driven insights, leading to improved financial performance.

Improving the customer experience with Amazon Lex and Amazon Polly

Insurance companies can further maximise their ROI by automating a wide range of customer-facing processes. AI-powered chatbots and virtual assistants, built on AWS services can provide customers with instant, personalised support at any time, improving their overall satisfaction and loyalty. This can lead to increased customer retention, whilst reducing operational costs. Another benefit is that by automating repetitive tasks, such as customer service inquiries or policy administration, employees are more available to focus on more strategic tasks.

Amazon Lex is a conversational AI service that enables insurance companies to build engaging and intelligent chatbots and virtual assistants. By leveraging Lex’s capabilities, insurers can automate a wide range of customer-facing processes, such as policy management, claims processing, and providing insurance quotes. This allows insurers to reduce operational costs and improve efficiency, as the service can handle routine inquiries and tasks without the need for human interaction. Additionally, Lex’s ability to provide personalised, contextual responses can enhance the customer experience, leading to increased satisfaction, loyalty, and retention.

One example is nib, a leading health insurer in Australia and New Zealand, which has leveraged Amazon Lex to build its chatbot. By using Amazon Lex, nib was able to automate a significant portion of its customer inquiries, with its chatbot now handling around 65% of all chat-based interactions. This has freed up nib’s contact centre agents to focus on more complex customer needs, while also improving the overall customer experience.

Complementing the chatbot functionality, Amazon Polly is a text-to-speech service that can be used by insurance companies to enhance their customer experience. By integrating Polly, insurers can provide customers with natural-sounding audio responses to their inquiries, whether it’s explaining policy details, walking through a claims process, or offering personalised recommendations. This can improve accessibility and convenience for customers, as they can receive information in an auditory format, rather than relying solely on written communication. Additionally, Polly’s ability to support multiple languages can help insurers serve a diverse customer base more effectively, therefore maximising ROI.

To conclude

In summary, embracing AI technologies in the insurance industry offers companies a competitive edge and the opportunity to maximise ROI. By enhancing operations and the customer experience with AI-powered solutions, insurers can streamline processes, reduce costs, and improve efficiency. This strategic approach positions companies for success and ensures long-term financial growth.

To learn more about how Firemind’s AI-driven solutions, powered by AWS can benefit your insurance company, please use the form below to get in touch