Provides an AI-driven claims management platform for health and life insurers, automating data acquisition, policy checks, medical coding, and fraud detection. The platform reduces claims processing costs by 10%, increases straight-through processing rates to 75%, and improves fraud detection hit rates to 72%, enabling insurers to enhance operational efficiency and reduce losses.
Funding
$45.2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
BCEFOCRVFounders
Product
Problem
Health and life insurers face challenges in efficiently managing claims due to manual data acquisition, policy checks, medical coding, and fraud detection processes. Inefficient claims processing leads to increased operational costs, slower processing times, and potential financial losses from fraud and inaccurate claims.
Solution
Qantev offers an AI-powered claims management platform designed to automate and streamline the end-to-end claims process for health and life insurance companies. The platform uses AI decision models for data acquisition, policy and coverage checks, medical coding, and consistency checks. By automating these processes, Qantev reduces claims processing costs, increases straight-through processing rates, and improves fraud detection accuracy. The platform's modular and adaptive architecture allows for continuous improvements and growth, ensuring insurers can optimize their claims operations and improve their bottom line.
Target Audience
Qantev primarily targets health and life insurance companies seeking to automate claims operations, reduce costs, improve efficiency, and enhance fraud detection capabilities.
Features
- AI-driven data acquisition from various claim document types and languages with OCR accuracy of 99% for printed and 90% for handwritten documents.
- Automated policy and coverage checks to ensure compliance and accuracy.
- AI-powered medical coding and consistency checks to reduce errors and improve efficiency.
- Fraud, waste, and abuse detection models to identify and prevent fraudulent claims.
- Network management tools to improve medical provider network performance through AI-driven insights and pricing gap detection.
- Customizable dashboards and reporting to track key performance indicators and identify areas for improvement.
- Integration with existing insurance systems and workflows for seamless implementation.