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Design, Results and Industry Implications of the World's First Insurance Large Language Model Evaluation Benchmark

arXiv — cs.CL•Wednesday, November 12, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The introduction of the CUFEInse v1.0 benchmark marks a significant advancement in the evaluation of large language models tailored for the insurance industry. This benchmark employs a robust framework comprising 5 core dimensions, 54 sub-indicators, and an impressive 14,430 high-quality questions, focusing on essential areas such as insurance knowledge and compliance. The evaluation of 11 mainstream models highlighted common deficiencies in general-purpose models, particularly their weak actuarial capabilities and inadequate compliance adaptation. Conversely, while domain-specific training demonstrated notable strengths in insurance-related scenarios, it also revealed challenges in adapting to business contexts. The establishment of this benchmark is crucial as it addresses the existing gap in professional evaluation tools within the insurance sector, paving the way for improved model performance and industry standards.
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