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InsureClaim AI

InsureClaim AI: Teaching LLMs to Investigate Before They Decide Insurance claims cost $40B annually.

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Core trick

Trains an LLM with GRPO in an OpenEnv environment to request evidence before approving claims, verifying income through the Plaid API.

Tags

financeagents

Description

InsureClaim AI: Teaching LLMs to Investigate Before They Decide Insurance claims cost $40B annually. LLMs rush to approve/deny without evidence—missing fraud. We built an RL environment training LLMs to process claims like expert adjusters. RESULTS: • +17.25 reward improvement over 50 episodes • Caught $13K inflated claims via Plaid verification • Reduced decision steps 6→3 while maintaining accuracy TECH: OpenEnv (10 actions, 8 scenarios) + Unsloth + TRL (GRPO) + Plaid API ALIGNMENT: • Statement 3.1: Professional Tasks (World Modeling) • Partner: Scaler AI Labs - Enterprise Workflows Results: drive.google.com/drive/folders/1QFQrJNM9mEOiPEnwV1CZjoENTSlGVvRI https://github.com/pramodmisra/claims-env-hackathon
pramodmisra/claims-env-hackathon★ 21 forksPythonMITCreated Mar 7, 2026 · last push Jul 27, 2026

README excerpt

---
title: Insurance Claims RL Environment
emoji: 📋
colorFrom: blue
colorTo: green
sdk: docker
app_port: 7860
pinned: false
license: mit
tags:
  - openenv
  - reinforcement-learning
  - insurance
  - enterprise-workflows
  - hackathon
  - rl-environment
---

# InsureClaim AI - Insurance Claims RL Environment

**OpenEnv Hackathon - Statement 3.1: Professional Tasks (World Modeling)**
**Partner Theme: Scaler AI Labs - Enterprise Workflows**

An RL environment for training LLMs to process insurance claims with realistic enterprise complexity, fraud detection, and Plaid API integration.

## Live Demo

- **HuggingFace Space**: https://pramodmisra-claims-env.hf.space
- **Health Check**: `curl https://pramodmisra-claims-env.hf.space/health`

## Training Results

| Metric | Value |
|--------|-------|
| Starting Reward | -5.5 |
| Final Average | **+11.75** |
| Improvement | **+17.25** |
| Best Episode | +17.4 (caught fraud) |
| Steps Reduction | 6 → 3 (50% faster) |

![Reward Curves](reward_curves.png)

## Overview

This environment simulates a real insurance claims processing workflow where an agent must:

1. **Gather Information** - Query policy details, claim history, fraud signals
2. **Verify Transactions** - Use Plaid API to verify purchase amounts
3. **Detect Fraud** - Identify inflated claims and staged accidents
4. **Make Decisions** - Approve, deny, or escalate claims efficiently

### Key Innovations

| Feature | Description |
|---------|-------------|
| **Partial Observabili

Team