Case Study

30% Faster Insurance Form Processing with Automation Enhances Customer Satisfaction

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Industry 

Insurance

Expertise 

Amazon S3, AWS Lambda, Amazon DynamoDB, Amazon API Gateway, Amazon Textract

Offerings/solutions 

Automation boosted efficiency, data quality, and customer satisfaction while cutting costs and handling increased volume.

About the Client

LIC Bangladesh is a leading global life insurance provider with a significant presence in South Asia. The client has a proven track record of serving millions of customers worldwide. With a strong financial foundation and a commitment to customer satisfaction, they have earned a reputation for trust and reliability in the insurance industry.

Highlights

20%

Increase in Customer Satisfaction

30%

Reduction in Processing Time

25%

Handling Increased Volume

The Challenge

The LIC team faces challenges with manual insurance form processing, including time-consuming tasks, frequent errors, and difficulties managing increasing form volumes. This leads to data inconsistencies, quality issues, and security risks. The manual approach causes inefficiencies and delays, impacting operational efficiency and accuracy. To overcome these issues, LIC aims to implement an automated solution for accurate data extraction and storage, partnering with CloudThat to develop an AI-powered OCR engine.

Solutions

• AWS Lambda provides serverless, scalable, and cost-efficient processing.
• Amazon S3 and DynamoDB ensure durability and performance for data storage.
• Amazon Textract extracts text from various document formats.
• Lambda functions automate processing and reduce latency.
• Data cleaning, validation, and enrichment occur within Lambda functions.
• Amazon API Gateway offers secure access to extracted data.
• AWS CloudTrail and CloudWatch monitor and provide performance metrics.
• Serverless architecture supports scalable and future-proof solutions.
• Pay-as-you-go pricing optimizes costs by charging only for used resources.

The Results

Automation reduced processing time by 30%, improved data consistency to 95%, and cut costs by 20% while handling 25% more volume.

Download the Case Study

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