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September 10, 2025International Journal of Scientific Research in Computer Science Engineering and Information TechnologyOpen Access

Advanced Data-Driven Frameworks for Intelligent Underwriting Risk Assessment in Property and Casualty Insurance

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Authors

RSRajkumar Govindaswamy Subbian

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Overview

Data-driven methods improve risk assessment in property and casualty insurance, suggesting enhanced profitability.

Key Points

  • Machine learning-based underwriting improves risk prediction accuracy by 35%, enhancing overall efficiency.
  • Premium calculation variability reduced by up to 25%, indicating significant advances in pricing precision.
  • This research analyzes over 100,000 policies, showcasing a robust application of predictive analytics.
  • The findings emphasize the importance of model interpretability and bias detection for regulatory compliance.

Cite This Study

Rajkumar Govindaswamy Subbian (2023) studied this question.

synapsesocial.com/papers/68c1e24d54b1d3bfb60ff73dhttps://doi.org/10.32628/cseit2342437
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