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Case Study 4.4

Precision Agriculture for Insurance Underwriters: Data Quality And Bias | 2021–2026 Trends

17
Pages
IEEE
Style
~ 18–27 mins
Reading Time
Governance MLOps InsurTech
Abstract

This case study investigates “Precision Agriculture for Insurance Underwriters: Data Quality And Bias | 2021–2026 Trends” using a survey-based structural equation modeling. Through a institutional lens, the analysis integrates multi-source data to derive novel empirical evidence for researchers and practitioners.

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Precision Agriculture for Insurance Underwriters: Data Quality And Bias | 2021–2026 Trends

ABSTRACT
Precision Agriculture for Insurance Underwriters: Data Quality And Bias | 2021–2026 Trends is unpacked across themes: usability, governance, scalability, and costs. Limitations and future research paths are noted.
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