Case study

Large Insurance Company Case Study

Transforming Insurance Operations with AI: A Case Study

Challenge

  • Enhancing knowledge access for employees to improve decision-making and customer service
  • Streamlining the contract review process, particularly for lengthy reinsurance agreements
  • Automating the generation of coverage letters for insurance claims to improve efficiency and consistency
  • Developing effective communication responses to objections to rate increases or other insurance actions
  • Analyzing claims data for reinsurance purposes and identifying potential risks and fraud

Opportunity

  • Harnessing the power of AI to unlock proprietary risk management information and enhance employee knowledge access
  • Utilizing AI to analyze and summarize complex documents, saving time across various departments
  • Automating the generation of coverage letters to reduce costs, improve efficiency, and ensure consistency in claims processing
  • Leveraging AI to generate persuasive and concise responses to objections, improving correspondence quality

How AVM's GenAI Platform Can Help

  • Training an AI model on the insurance companies proprietary risk management information using Claude/GPT-4
  • Implementing a "Chain of Entity" prompt chain to analyze and summarize lengthy PDFs using Claude/GPT-4
  • Automating the generation of coverage letters for insurance claims using Claude/Bard/GPT-4
  • Developing communication responses to objections using Claude/GPT-4
  • Analyzing claims data for reinsurance purposes using GPT-4

How AVM Solves the Problem for the Industry

  • Improves employee decision-making and customer service by providing access to previously expert-only information
  • Streamlines the contract review process, saving time and improving decision-making
  • Reduces costs, improves efficiency, and ensures consistency in claims processing by automating coverage letter generation
  • Speeds up response time and improves content quality when addressing objections to rate increases or other insurance actions
  • Provides real-time insights for data analysis, fraud detection, and risk management by filtering and analyzing claims data

Benefits to the Company and Its Customers

  • Increases employee engagement, with 50% of licensees in key departments using the AI-powered knowledge access tool
  • Reduces time needed to analyze and summarize documents, increasing the efficiency of related workflows
  • Achieves a 50% reduction in time needed to generate coverage letters, with minimal errors and unhelpful responses
  • Improves the persuasiveness and conciseness of correspondence, making it easier for employees to respond to objections
  • Identifies potential risks, fraud, and claims to be combined, leading to tangible financial savings for the company