Poor data quality & inaccuracy across the chain

Data flowing between insureds, agencies, carriers and vendors is messy, inconsistent and often outright wrong, undermining reporting, AI projects and underwriting confidence.

Analysis:

Data quality infrastructure for insurance — validation, normalization, enrichment — is foundational to every AI and analytics initiative in the industry. A company that becomes the trusted data layer across the insurance value chain would have enormous strategic value. This is infrastructure that enables everything else.