Automating Insurance Claims using Natural Language Processing

CASE STUDY

CLIENT |  Swiss insurance company
INDUSTRY | Insurance
DATE | 2016 - 2017

Overview

This case study showcases the successful implementation of an automated system for triaging, routing, and extracting relevant information from paper-based insurance claims for a Swiss insurance company. The implementation led to a 40% automation ratio, allowing the company to better manage their high volume of claims.

Customer Profile

The customer is a well-established Swiss insurance company offering a wide range of insurance products, including health, life, and property insurance. Due to their diverse portfolio, the company processes a significant number of paper-based insurance claims daily.

Challenge

The Swiss insurance company faced several challenges due to the high volume of paper-based insurance claims they received. These challenges included:

1. Time-consuming manual processing of claims, which led to delays in claim resolutions and increased customer dissatisfaction.
2. Difficulty in managing the increasing volume of claims, resulting in backlogs and operational inefficiencies.
3. Increased likelihood of human error in claim evaluation and processing, potentially leading to incorrect claim decisions.

Approach

To address these challenges, the insurance company decided to automate the process of triaging, routing, and extracting relevant information from paper-based insurance claims. The approach involved:

• Implementing Optical Character Recognition (OCR) technology to convert the paper-based claims into digital data.
• Developing a rule and machine learning based system to classify and route the digital claims data based on predefined criteria, such as claim type, claim amount, and complexity.
• Utilizing Natural Language Processing (NLP) and Machine Learning (ML) algorithms to extract relevant information from the digital claims data, including policy numbers, claimant details, and supporting documents.
• Integrating the automated system with the company's existing claim management software to ensure seamless data transfer and processing.

Results

After implementing the automation solution, the Swiss insurance company achieved the following results:

• A 40% automation ratio in processing paper-based insurance claims, significantly reducing manual intervention and enabling the company to handle higher claim volumes.
• Faster claim processing times, leading to quicker resolutions and improved customer satisfaction.
• Reduction in human error and increased accuracy in claim evaluations, ensuring fair and accurate claim decisions.
• Enhanced operational efficiency due to streamlined processes, allowing employees to focus on more complex and value-adding tasks.

Conclusion

By automating the process of triaging, routing, and extracting relevant information from paper-based insurance claims, the Swiss insurance company effectively addressed their challenges and significantly improved their claim management operations. The successful implementation of this solution demonstrates the potential benefits of automation in the insurance industry, particularly for companies that deal with high volumes of claims.