Description

We are seeking to develop an AI-powered Insurance Underwriting & Claims Automation Agent that streamlines risk assessment, policy underwriting, fraud detection, and claims decision workflows for insurance providers.

The solution will leverage Artificial Intelligence and Machine Learning to automate risk profiling, premium estimation, policy recommendations, document extraction, and real-time claims validation.

The objective is to reduce underwriting turnaround time, minimize fraud losses, improve claim accuracy, and enhance customer experience through intelligent automation.

Key Requirements

• AI conversational assistant for insurance applicants

• Automated risk profiling based on applicant data

• Policy recommendation engine using ML

• Premium pricing optimization model

• Intelligent document extraction (ID, medical records, claim forms)

• Claims automation workflow with fraud detection

• Real-time underwriting decision support

• Explainable AI scoring for regulatory transparency

• Commission tracking for agents/brokers

• Scalable multi-tenant architecture

Expected Workflow

1. User interacts with AI agent for insurance inquiry.

2. AI collects demographic, financial, and health/risk data.

3. Risk scoring engine evaluates underwriting risk profile.

4. Premium pricing model generates optimized pricing options.

5. Policy options are ranked and recommended.

6. Documents are uploaded and auto-processed via NLP/OCR.

7. Claims are evaluated using AI risk & fraud models.

8. Approval or manual review is triggered intelligently.

9. Analytics dashboard updates in real time.

Platform Architecture

AI Agent Layer (LLM + NLP Extraction)

• Conversational requirement capture

• Structured data extraction

• Compliance-aware communication

Risk Scoring Engine (ML Microservice)

• Classification models for underwriting risk

• Predictive claim probability scoring

• Feature engineering based on actuarial principles

Premium Optimization Engine

• Dynamic pricing model

• Risk-adjusted premium calculation

• Profitability-aware recommendations

Fraud Detection Module

• Behavioral anomaly detection

• Claim pattern analysis

• Outlier flagging using statistical + ML models

Insurance Analytics Dashboard

• Underwriting turnaround metrics

• Claim approval rates

• Fraud detection rate

• Agent performance tracking

• Portfolio risk exposure visualization

Intelligent Risk Scoring Model

Underwriting Score =
(Risk Profile × 0.40) +
(Financial Stability × 0.20) +
(Claim History × 0.20) +
(Policy Fit × 0.10) +
(Compliance Score × 0.10)

The scoring engine includes explainability insights for regulatory transparency.

Customer Expectations

• Delivery timeline: 4 weeks
• Automated underwriting decisions
• Real-time claims processing
• Reduced fraud exposure
• Transparent risk scoring
• Enterprise-grade scalability
• Compliance-ready AI architecture

Skills Required

• Artificial Intelligence & Deep Learning

• Machine Learning (Risk Modeling)

• Natural Language Processing (NLP)

• API Integration

• Fraud Detection Systems

• Financial AI Compliance

• Data Analytics & Dashboard Development

• Automation & Microservices Architecture