工程机械设备风险评估模型

该模型是一款基于大数据技术和机器学习技术用于工程机械保险场景的标签式评分产品，结合了机械之家积累的海量产业数据，联合保司历史投保及赔付数据，构成一套由多元样本为基础的数据模型，通过C4.5决策树算法加工，形成事实还原和风险预测的评分系统，经验证每年可为保司有效降低赔付20%，预期可每年帮助保险公司降低保险赔付上亿元

This model is a labeled scoring product based on big data and machine learning technologies, tailored for the construction machinery insurance scenario. It combines massive industrial data accumulated by Jixie Home and historical insurance application and claims data from insurance companies, establishing a data model built on diverse samples. Processed using the C4.5 decision tree algorithm, it forms a scoring system for fact restoration and risk prediction. Verified practical applications have shown that it can effectively reduce insurance claim payouts by 20% annually for insurance companies, and is expected to help insurers cut annual insurance claim expenditures by hundreds of millions of yuan.

搜集汇总

背景与挑战

背景概述

该数据集是基于工程机械产业数据和保险历史数据构建的机器学习模型，采用C4.5决策树算法进行风险评估，经验证可有效降低保险公司赔付金额20%。