- Entity extraction on relevant facts of key documents such as police reports.
- Entity resolution to deduke claim data to arrive at a single view of insured
- Early detection of total salvage
- Integrate subrogation predictions directly into existing claims workflows
Safekeep
As a Zurich Global Gold Award Winner and Efma-Accenture Global Silver Award Winner, Safekeep uses machine learning to help achieve efficiencies and improve outcomes, enhancing the claims experience for insurers and policyholders alike.
Safekeep has partnered with global top-tier commercial lines carriers and insurtechs across all segments and lines of business. Safekeep leverages proprietary machine learning models as well as patented semantic search capable Natural Language Processing, Entity Resolution, and statutory rules-based automation to ingest claims files, quickly analyze details and evidence, then integrate subrogation decisions into existing claims workflows. This AI-powered process streamlines subrogation management, contributing to improved accuracy at scale, lower cycle times, and accelerated resolutions.
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Advantages
Features
- Execute and manage over 4,000 regulatory rules curated and automated out-of-the box.
- Configure special handling rules specific to commercial policyholders who want to execute exceptions to subrogations rules.
- Process claim notes to automatically detect claimants, medical providers, liable third parties, attorneys, injury types, and causes of loss.
- Ingest both unstructured and structured data in batch (SFTP) or real time via APIs.
Expertise
- Each of our team members come from the insurance industry and have deep expertise in data science, lean six sigma, and subrogation
- Among over 1,350 companies, Safekeep was selected by Zurich as the Gold Winner in their Innovation Championship