Insurance

Palantir’s insurance solutions enable comprehensive data integration and advanced analytics to improve risk assessment, streamline claims processing, and personalize customer experiences.

By leveraging real-time insights, insurers can make data-driven decisions that enhance operational efficiency and customer satisfaction.
Explore the Use Cases

Use Case 1AIP Claims Coverage Engine

AIP Claims Coverage Engine empowers insurance providers to provide accurate, consistent claim coverage assessments, leading to faster claim processing and improved customer satisfaction. By rapidly comparing claims against user-defined coverage conditions, AIP offers a quick and accurate determination of coverage, enhancing efficiency and reducing operational costs.
Overview

AIP rapidly accelerates the coverage review process by streamlining the evaluation of insurance claims against established coverage conditions, while simultaneously putting human-in-the-loop guardrails in place to enforce the ethical use of AI. With the ability to understand natural language descriptions and images, users can effortlessly modify the enforced conditions to fit their specific requirements. This accelerates the core operations of insurance companies, significantly reducing the time and expense associated with claim handling.

By harnessing AIP, insurance providers can ensure more accurate, consistent claim coverage assessments, leading to faster claim processing and improved customer satisfaction. The system’s adaptability allows for quick adjustments to coverage conditions, making it an indispensable tool for keeping pace with changing regulations and insurance products.
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Claims Ingestion

Users can start immediately with a selection of notional customer claims or ingest their own claims to run through the customizable coverage engine.

Multimodal-AI-powered Review

AIP leverages multimodal AI to automatically assess incoming claims against pre-defined and customizable coverage conditions, ensuring a rapid and accurate determination of coverage eligibility.

Dynamic Reporting

The system provides dynamic reporting features, allowing users to easily review and validate the results of the coverage checks for each claim. This transparency helps in making informed decisions and streamlining the claim coverage review process.

Ethical AI Guardrails

AIP automatically puts guardrails in place which make sure that the AI is never permitted to prevent the payout of a claim without a human confirming the correctness of its determinations.

Use Case 2AIP Property Insurance Underwriting Assistant

AIP helps underwriters analyze insurance submissions by flagging potentially detrimental features and conducting checks for standard compliance.
Overview AIP helps teams extract and organize data from incoming property insurance submissions, enabling underwriters to rapidly make sense of complex risk information, flag potentially detrimental features, and ensure standard compliance in underwriting.
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Extract relevant data

Extract relevant data from property insurance submissions and appropriate records while maintaining the necessary sourcing to the underlying documents.

Automatically detect and flag

AIP allows organizations to integrate external data sources, such as SEC filings and news articles, to enhance their underwriting process.

Generate Response

AIP enables underwriters to generate suggested responses to broker/agent based on a combination of automated flags generated and Human-In-The-Loop interventions.

Use Case 3AIP for Portfolio Risk Trends & Management

AIP enhances portfolio management by helping users investigate rate and exposure trends and apply these insights to existing risk portfolios.
Overview

AIP enhances portfolio management by helping users investigate rate and exposure trends, and apply these insights on existing risk portfolios.
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Granular Portfolio Management

Analyze performance at every level of portfolio, and against capital allocation, to identify risk and policy volume.

Macro Portfolio Management

AIP allows users to enhance the Ontology with external public data sources, for example trend information from news articles, industry reports and internal meeting note. This enables portfolio managers to contextualize macro events and trigger portfolio actions.