Insursight AI provides an AI‑driven analytics platform for insurers that predicts per‑customer lifetime value and acquisition cost, generates risk‑adjusted pricing recommendations, and automates claims underwriting with data extraction, fast‑track segmentation, and fraud scoring. The platform integrates internal and external data, offers an interactive dashboard and API endpoints, helping property‑casualty, life, and reinsurance companies improve underwriting, pricing, and claims profitability.
Funding
Funding not disclosed
Founders
Product
Problem
Insurance companies struggle to accurately estimate monetary risk, customer lifetime value (CLV) and acquisition costs (CAC), and to process claims efficiently, leading to suboptimal pricing, profitability, and fraud detection.
Solution
Insursight.ai delivers an AI-driven analytics platform that predicts individualized CLV and CAC, enabling insurers to assess unit economics on a per‑customer basis. The system applies high‑dimensional, non‑linear models that incorporate internal data and external factors such as seasonality and market indices. It also provides smart costing and pricing tools that generate risk‑adjusted price recommendations. For claims underwriting, the platform automates data extraction, segments claims for fast versus investigative tracks, and flags potentially fraudulent submissions. All predictions and insights are presented through an interactive dashboard that supports data‑driven decision making across underwriting, pricing, and claims operations.
Target Audience
Primary customers are property and casualty insurers, life insurers, and reinsurance firms that need advanced analytics for underwriting, pricing, and claims management.
Features
- Predictive models for per‑customer CLV and CAC using deep learning and non‑parametric probabilistic techniques
- Dynamic pricing engine that produces risk‑adjusted price suggestions based on real‑time loss cost forecasts
- AI‑powered claims underwriting workflow with automated data extraction, fast‑track vs investigative segmentation, and fraud risk scoring
- Integration of external variables (e.g., seasonal trends, market indices) to enhance prediction accuracy
- Interactive dashboard for visualizing unit economics, profitability ratios, and claim‑processing metrics
- API endpoints for seamless embedding of predictions into existing underwriting and policy management systems