Reimagining Risk and Claims with AI

The problem

Commercial underwriters review 100+ pages of documents per submission, financial statements, loss runs, applications, and supplemental data. Manual data extraction and risk assessment take 5-7 days per submission, and underwriter capacity limits quote volume. Inconsistent risk selection across underwriters leads to adverse selection and unprofitable books of business.

How we approach it

Deploy an AI workbench that automatically extracts data from submissions, enriches risk profiles from external sources, generates risk scores with full explainability, and presents underwriters with pre-analyzed submissions and recommended actions. Underwriters focus on judgment and relationships while AI handles data processing.

The problem

45% of claims require manual handling despite being straightforward, first notice of loss intake, document collection, coverage verification, and damage assessment all involve human reviewers. Average claims cycle time is 15-20 days, frustrating policyholders and driving up per-claim handling costs. Adjusters spend time on routine claims instead of complex ones that need expertise.

How we approach it

Automate the claims lifecycle for eligible claims with AI that handles FNOL intake, extracts information from photos and documents, validates coverage, assesses damage, and initiates payment, all with human oversight for exceptions. Straight-through processing settles simple claims in minutes while routing complex claims to experienced adjusters.

The problem

Insurance fraud costs the industry $80 billion annually.10% of claims involve some form of fraud. Traditional rules-based detection catches obvious cases but misses sophisticated organized fraud rings. SIU teams are overwhelmed with false positives while real fraud networks operate across multiple claims, claimants, and providers. Individual claim review cannot detect coordinated schemes.

How we approach it

Deploy graph neural networks that analyze relationships across claims, claimants, providers, and entities to detect organized fraud patterns. Our system identifies suspicious networks, scores claims for fraud risk, and provides SIU investigators with visualized evidence and explainable alerts, dramatically improving detection rates while reducing false positives.