Industries
Insurance
Pricing, claims and underwriting analytics with actuarial rigour.
Overview
Insurers rely on statistical models to price risk, assess claims and manage reserves. Modern data sources and techniques can improve these, provided they remain transparent and fair.
Common challenges
- Long, uncertain claim development
- Fairness and regulatory scrutiny of pricing factors
- Fraud and leakage in claims
- Legacy policy administration systems
Where AI and data science help
Pricing analytics
Support actuarial teams with modelling and monitoring.
Claims triage
Prioritise and route claims for faster handling.
Fraud detection
Identify unusual patterns for investigation.
Document processing
Extract data from claim forms and reports.
Typical data sources
- Policy and exposure data
- Claims history
- Third-party reference data
- Documents and images metadata
Responsible use
Rating variables must comply with applicable regulation and fairness requirements, and we document how each factor is used.
Bring us a decision you want to improve.
Tell us about the problem and the data you have. We will reply with a candid view of where we can help.