Agentic AI-Powered Digital Underwriting: 95%+ Accurate Risk Decisions under 40 Seconds

A leading life insurance provider, offering a wide range of protection, savings, and investment products to millions of customers across various countries. With a large and growing customer base, the organization processes high volumes of life insurance policy applications every month and focuses on delivering efficient, compliant, and customer-centric insurance services.

The Challenge: Scaling Life Insurance Underwriting with Speed & Accuracy

With over 40,000 life insurance applications every month, client faced growing pressure to accelerate medical underwriting while maintaining accuracy and compliance. The existing process relied heavily on manual review of medical reports, risk evaluation, and fraud verification, making it time-consuming and difficult to scale.

Underwriters had to assess complex medical data, verify the authenticity of diagnostic reports, and ensure compliance with company medical guidelines for each application. This increased operational workload, slowed decision-making, and created challenges in maintaining consistent risk evaluation. The organization needed an intelligent solution that could automate medical risk assessment, detect fraud, ensure 100% compliance with underwriting rules, and significantly reduce processing time without compromising accuracy.

The Solution: Multi-agent Intelligent Digital Underwriting

To address underwriting challenges, a multi-agent AI underwriting system was implemented. The platform uses multiple specialized AI agents that work together to automate medical evaluation, fraud detection, compliance validation, and underwriting decisions.

AI Agents Driving the Solution:

• Document Analysis Agent

 Extracts and structures medical data from lab reports, MER, CBC, ECG, and other diagnostic documents through integration with Intelligent Document Processing (TruCap+). It converts unstructured medical records into standardized data for further analysis. 

• Medical Assessment Agent

 Performs comprehensive health evaluation by calculating BMI, analyzing Complete Blood Count (CBC) and Differential Leukocyte Count (DLC), evaluating lipid profiles, diabetes markers (HbA1c), and liver and kidney function tests. The agent computes a health score and flags normal or abnormal values to enable consistent medical risk assessment. 

• Fraud Detection Agent

 Identifies suspicious cases by verifying diagnostic centres against blacklists and performing geographic distance analysis between the customer’s address, diagnostic lab, and geotag data. Configurable thresholds classify fraud risk levels (low, medium, high), strengthening underwriting integrity. 

• Rule Intelligence Agent

 Uses LLM-powered parsing to interpret company underwriting guidelines and age–sum assured medical grids. It ensures automatic compliance validation, supports dynamic rule updates without code changes, and maintains version control with rollback capability. 

• Decision Support Agent

 Consolidates insights from all agents to categorize applications into risk levels (low, moderate, high), generate underwriter notes, and recommend actions for cases requiring manual review, enabling faster and consistent decision-making. 

Technology Foundation

The solution is powered by a robust technology stack that enables scalable and intelligent underwriting. It uses a multi-agent architecture where specialized AI agents collaborate through the CrewAI framework, ensuring structured workflows and reliable outputs. Large Language Models (Claude/GPT) drive intelligent rule parsing and risk evaluation, while seamless integration with the TruCap+ Intelligent Document Processing platform enables automated data extraction from medical documents.

The API-first design allows easy dashboard and frontend integration, ensuring flexibility, scalability, and enterprise-ready deployment. Together, these technologies enable automated, accurate, and scalable digital underwriting with faster processing, stronger compliance, and improved risk governance.