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Automated Medical Cost Refund Processing System with AI-Driven Email Intake and Flexible Workflow
  1. case
  2. Automated Medical Cost Refund Processing System with AI-Driven Email Intake and Flexible Workflow

Automated Medical Cost Refund Processing System with AI-Driven Email Intake and Flexible Workflow

altkomsoftware.com
Insurance
Medical

Challenges in Medical Cost Refund Request Management and Claims Automation

The client faces difficulties handling increasing claims processing costs due to limited system flexibility, with many refund requests submitted via email rather than through structured online forms. This necessitates manual verification, data extraction, and case classification by claims adjusters, leading to inefficiencies and delays. The existing core systems lack adaptable process modeling and automation capabilities, impeding operational efficiency and customer experience.

About the Client

A large insurance company specializing in health insurance services seeking to optimize claims processing workflows and enhance automation capabilities.

Goals for Enhancing Claims Processing Efficiency and Automation

  • Develop a digital online form to streamline medical cost refund requests and reduce manual processing.
  • Implement a flexible workflow engine allowing the insurance company to customize claim processing pathways without additional development.
  • Create an internal adjuster application to support review, approval, and rejection of claims, providing real-time visibility into claim status.
  • Integrate an AI module capable of analyzing customer emails to automate data extraction and request registration, automating up to 80% of common queries.
  • Enable claims processing automation to significantly decrease manual effort, reduce processing time, and improve customer satisfaction.

Core Functional Components for Claims Automation and Management

  • Online submission form converting paper refund requests into digital format.
  • Workflow engine allowing insurance staff to define and modify end-to-end claim processing steps based on decision rules such as spending limits and product-specific rules.
  • Backoffice adjuster application to view, review, accept, or reject claims submitted via online form or email, with real-time updates.
  • AI-powered email analysis component that examines incoming customer messages to automatically populate claim details and classify requests for further processing.
  • Automated request forwarding from AI module, with manual review optional for claims flagged as uncertain or requiring additional data.

Recommended Technology Stack for Claims Automation

Spring Boot / Java 17 for backend development
Workflow engine such as Camunda for process modeling and management
AI/LLM platforms for natural language processing and email analysis
Cloud service providers like AWS for AI/ML model hosting (e.g., AWS Bedrock, SageMaker)

External Systems and Data Sources Integration Needs

  • Insurance core claims management system for data synchronization
  • Customer communication channels (email system) for email processing
  • Decision rule databases for workflow routing logic
  • User authentication and authorization platforms for secure access

Key Non-Functional System Attributes

  • System must support scalable processing to handle increasing request volumes with minimal latency.
  • Real-time or near-real-time processing for email analysis and claim routing.
  • High security standards to protect sensitive health and personal data, complying with relevant regulations.
  • Availability of 99.9% uptime and fault-tolerance to ensure continuous operation.

Projected Business Benefits and Efficiency Gains

The project aims to enable automation of up to 80% of common medical refund inquiries, leading to substantial operational efficiency, faster claims processing times, and improved customer satisfaction. The flexible workflow system will allow the client to rapidly adapt to changing procedures and regulations without significant redevelopment, reducing processing costs and increasing process transparency.

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