Ai-enabled search and discovery for claims processing and fraud detection

Whitepaper
Premium Content

Insurance carriers can gain an advantage over competitors by introducing AI into their workflows and reducing the time it takes to approve a claim without decreasing the accuracy that data is entered into their system.

AI-Enabled Search and Discovery for Claims Processing and Fraud Detection

Large insurance companies have been experimenting with Artificial Intelligence (AI) since the middle of the 2010s, piloting chatbots and collecting telematics data for future AI projects. The insurance industry more than many others relies on the collection of data to make critical business decisions. Whether writing policies, or processing claims efficiently the way insurers employ data will determine the lifetime value of the customer.

In this whitepaper, you will learn:

  • How AI can save time by auto classifying and normalizing input data from multiple source formats (video, physical paper, pictures etc.) into the carriers’ systems for a comprehensive analysis
  • Why increased accuracy from using AI, insurance carriers can save on claims processing costs, including overhead expenses for outsourced data entry
  • How claimants could receive their payments quicker, which could increase their brand loyalty

One possible first step toward taking advantage of AI in insurance lies in understanding what Emerj, the AI research company, calls the AI Opportunity Landscape: a map of what is possible and what is working with AI in a given industry. As part of their recent focus on insurance, Emerj found that 46% of AI companies in insurance provide solutions for claims.

In this whitepaper, Emerj explains the importance of digitizing data to ensure the completeness and accuracy of all information and company data. Recent use cases will be shown to highlight the importance of using an AI/ML program to strengthen all business processes.

Large insurance companies have been experimenting with AI since the middle of the 2010s, piloting chatbots and collecting telematics data for future AI projects. The insurance industry more than many others relies on the collection of data to make critical business decisions. Whether writing policies, or processing claims efficiently the way insurers employ data will determine the lifetime value of the customer.

One possible first step toward taking advantage of AI in insurance lies in understanding what Emerj, the AI research company, calls the AI Opportunity Landscape: a map of what is possible and what is working with AI in a given industry. As part of their recent focus on insurance, Emerj found that 46% of AI companies in insurance provide solutions for claims.

 

Large insurance companies have been experimenting with AI since the middle of the 2010s, piloting chatbots and collecting telematics data for future AI projects. The insurance industry more than many others relies on the collection of data to make critical business decisions. Whether writing policies, or processing claims efficiently the way insurers employ data will determine the lifetime value of the customer.

One possible first step toward taking advantage of AI in insurance lies in understanding what Emerj, the AI research company, calls the AI Opportunity Landscape: a map of what is possible and what is working with AI in a given industry. As part of their recent focus on insurance, Emerj found that 46% of AI companies in insurance provide solutions for claims.