基于数据挖掘的扶贫对象精准识别研究

Research on Accurate Recognition of Poverty Reduction Objects Based on Data Mining

贫困户人员多、居住分散,资金需求具有小、急、频等特征,造成贫困户容易成为金融机构排斥对象。本文以贫困地区信用建设为突破口,利用大数据分析和挖掘技术对农户的基本信用进行评级,根据信用等级及主要影响因素确定扶贫资金的额度,有针对性的定制金融产品。这样一方面提高了金融机构扶贫的精准度,另一方面可以大大提升金融机构参与扶贫的积极性,使得农村金融生态环境越来越好。

The number of poor households is scattered, and the demand for funds is small, urgent and frequent,which makes poor households easy to be excluded from financial institutions. This paper takes credit construction in poor areas as a breakthrough, uses large data analysis and mining technology to evaluate the basic credit of farmers, and determines the amount of the poverty alleviation funds according to the credit rating and the main factors, and there are targeted customized financial products. On the one hand, the precision of financial institutions＇ poverty alleviation is improved, on the other hand, the enthusiasm of financial institutions to participate in poverty alleviation can be greatly improved, and the rural financial ecological environment is getting better and better.