Risk-Informed Machine Learning Models for Renewal Classification in Motor Insurance

This study develops an interpretable machine learning framework for type 1 motor insurance renewal classification using 70,290 real-world Thai policies, providing essential insights for pricing, customer retention, and operational decision making. The dataset was partitioned into a 70% training set,...

תיאור מלא

מידע ביבליוגרפי

Principais autores:	Pichit Boonkrong, Junwei Yang, Xueyuan Huang, Teerawat Simmachan
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	MDPI AG 2026-03-01
סדרה:	Risks
נושאים:	customer retention analysis feature selection motor insurance analytics risk assessment SHAP explainability
גישה מקוונת:	https://www.mdpi.com/2227-9091/14/3/57
תגים:	הוספת תג אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!