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Dissertation 4.6

Roi And Performance Metrics in Natural Language Processing for Insurance Underwriters: A Comparative Perspective

19
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Harvard
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~ 20–30 mins
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Energy Education Marketing
Abstract

This dissertation investigates “Roi And Performance Metrics in Natural Language Processing for Insurance Underwriters: A Comparative Perspective” using a propensity score matching. Through a economic lens, the analysis integrates multi-source data to derive a validated measurement model for researchers and practitioners.

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Roi And Performance Metrics in Natural Language Processing for Insurance Underwriters: A Comparative Perspective

ABSTRACT
Roi And Performance Metrics in Natural Language Processing for Insurance Underwriters: A Comparative Perspective is unpacked across themes: benefits, usability, risks, and change enablement. Limitations and future research paths are noted.
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