基于大数据分析算法的农民数字普惠金融行为研究

Ziqing Xia, Weilun Huang
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摘要

本文的目的是在文献综述和问卷调查结果的基础上,结合大数据分析算法、方差分析、回归分析、效应分析等方法,探讨农村地区数字金融金融的发展情况,研究居民每月信用贷款的频率,研究受教育程度、月收入、金融机构的优劣势等。根据相关性分析和数据模型拟合的结果,年龄、对金融机构优势的认知显著影响居民平均每月使用信用贷款的频率和居民数字普惠金融获得的融资额。政府和金融机构可以参考研究和建议,优化政策,改善目前存在的问题,加快金融创新的速度,促进普惠金融的快速发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The study on farmer’s digital inclusive financial behavior by big data analysis algorithms
The aim of this paper is based on the results of the literature review and questionnaires,combined with the methods of big data analysis algorithms,analysis of variance, analysis of regression, analysis Of Effects and other methods to explore the development of digital financial finance in rural areas, studies the frequency of residents' monthly credit loans, studies the education level, monthly income, and the advantages and disadvantages of financial institutions. According to the results of analysis of correlation and data model fitting, age, cognition of the advantages of financial institutions significantly affect the frequency of residents 'average monthly use of credit loans and residents' digital inclusive finance Amount of financing obtained. The government and financial institutions can refer to the research and suggestions to optimize the policies, improve the current existing problems, accelerate the speed of financial innovation, and promote the rapid development of inclusive finance.
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