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September 10, 2025International Journal of Computational and Experimental Science and EngineeringOpen Access

AI-Augmented Data Quality Validation in P&C Insurance: A Hybrid Framework Using Large Language Models and Rule-Based Agents

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Authors

SMShreekant MalviyaVPVrushali Parate

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Overview

Hybrid methodology demonstrates improved data quality validation in P&C insurance, indicating greater efficiency and compliance.

Key Points

  • The framework enhances data quality validation by identifying schema mismatches and format problems effectively.
  • Utilizing a large language model, the system automates schema-aware YAML rule generation and issue summaries.
  • The modular design allows for flexibility, enabling adaptation to domains like retail and healthcare for data quality challenges.
  • The agentic architecture balances the need for compliance with the operational reliability of data governance solutions.

Cite This Study

Malviya et al. (2025) studied this question.

synapsesocial.com/papers/68c1afd354b1d3bfb60e7fc1https://doi.org/10.22399/ijcesen.3613
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