A Tabular Foundation Model For Smarter Insurance Decisions
TabPFN understands your underwriting, claims, and customer data; delivering faster, more accurate predictions. Make your data science workflows 90% faster.
High Impact Insurance Use Cases
Why Insurers Pick TabPFN
Fast To Value
Zero to prediction in seconds with zero-shot predictions and faster workflows.
Fine-Tuning
Optional fine-tuning on your proprietary data for domain adaptation and lift.
Synthetic Data
Privacy-preserving synthetic data generation to augment scarce or sensitive datasets.
Explainable And Fair
Feature-level impacts, partial dependence, example-based explanations to support fairness and compliance.
Explore 10 real-world insurance examples.
Context & Outcome
This dataset combines demographic, regional, and detailed vehicle specifications to predict whether a claim will occur for a motor policy. The sample includes tens of thousands of policies with diverse coverage contexts.
TabPFN generates strong claim risk scores without manual tuning, giving pricing teams more accurate exposure estimates and helping investigations focus on the riskiest cases to reduce leakage.
Task: Classification | Features: 43 | Rows: 58.6K (10K subsample) | Target: is_claim
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