State Auto Improves Processes across the Life Cycle Using AWS Machine Learning, Computer Vision, and Serverless Architecture
State Automobile Mutual Insurance Company (State Auto) wanted to better understand and anticipate the requirements of its customers to provide them with the information they needed before they even knew to ask for it. The company began using technology to help its customer service representatives (CSRs) meet quality and customer satisfaction score goals when it built its SA360 solution on Amazon Web Services (AWS). By using data-fueled insights and making these insights available to customers and CSRs, State Auto was able to build a better service experience, redirecting typical customer calls to self-service channels so that CSRs were able to focus on those customers with more complex needs. Following the success of this project, State Auto began using more AWS services, including machine learning (ML), computer vision, and serverless services, to help further its goals in other areas such as the automation of the underwriting processes and early detection of fraudulent claims to expedite case review.
Because AWS services do their job so well out of the box, we have the flexibility to be creative and build things on top of them."
Vice President of Strategic Technology Research, State Automobile Mutual Insurance Company
Exploring Service Optimization Using AWS
Implementing Customer-Focused Workflow Optimization
By using managed services for computer vision from AWS, State Auto has been able to automate processes that it previously performed manually. To simplify the property inspection process, the company uses Amazon Rekognition, which automates image and video analysis with ML and offers pretrained and customizable computer vision capabilities to extract information and insights. State Auto is able to use Amazon Rekognition to tag non-industry-specific risk factors in photos and videos from property inspections, giving risk engineers more time to focus on identifying industry-specific aspects in their risk assessments. To train State Auto’s ML models, the company extensively used Amazon SageMaker Ground Truth, a data labeling service. After the model went live, the company also used Amazon Augmented AI (Amazon A2I)—an ML service that makes it simple to build the workflows required for human review—for active user validation.
State Auto also uses Amazon Textract—which automatically extracts printed text, handwriting, and data from scanned documents—to index documents using a wide variety of business optimization use cases. “Our use of Amazon Textract touches almost every step in the insurance life cycle,” says Ramanujam.
Beyond managed services, State Auto is also using serverless architecture to power its antifraud solution, which combines the expertise of the company’s business users with data-driven insights. The solution was built on AWS Lambda—a serverless, event-driven compute service that lets companies run code for an application or backend service without provisioning or managing servers—and uses AWS Step Functions. The whole solution was seamlessly brought together using AWS Glue—a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, ML, and application development. After a hassle-free deployment of the fraud detection service, State Auto can now assess 83 percent more total claims for potential fraud than before, identify suspicious claims 3 days earlier in the claims process, and catch the 20 percent of claims that would previously have gone unflagged.
Using AWS to Standardize Operations
Building solutions using AWS resources has increased operational efficiency for State Auto by empowering the company to address its customers’ needs more directly, and the company continues to see the benefits. “Using AWS services has increased our overall agility and flexibility in developing solutions and facilitated a faster, less costly, and better delivery of our capabilities across the board,” says Skaggs.
About State Automobile Mutual Insurance Company
Benefits of AWS
- Increased number of claims reviewed for potential fraud by 83%
- Mitigated an estimated $800,000 in service operating expenses
- Facilitates detection of fraud 3 days earlier
- Increased operational efficiency
AWS Services Used
Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from scanned documents. It goes beyond simple optical character recognition (OCR) to identify, understand, and extract data from forms and tables.
Amazon Transcribe is an automatic speech recognition service that makes it easy to add speech to text capabilities to any application. Transcribe’s features enable you to ingest audio input, produce easy to read and review transcripts, improve accuracy with customization, and filter content to ensure customer privacy.
AWS Step Functions
AWS Step Functions is a low-code, visual workflow service that developers use to build distributed applications, automate IT and business processes, and build data and machine learning pipelines using AWS services. Workflows manage failures, retries, parallelization, service integrations, and observability so developers can focus on higher-value business logic.
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