“TrustScore” fintech machine-learning: growing the UK economy from enabling underserved communities to access mainstream financial services by building a credit-file through their established practice of saving clubs
“TrustScore” fintech machine-learning: growing the UK economy from enabling underserved communities to access mainstream financial services by building a credit-file through their established practice of saving clubs
批准号:
10052433
负责人:
金额:
$25.41万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
点击翻译按钮获取中文摘要
英文摘要
Exclusion from financial-services blights the lives of millions in the UK. It damages the UK economy: creating financial-insecurity, stunting entrepreneurism, increasing unemployment, social security and healthcare costs.Lack of a credit-rating is a key barrier to financial-inclusion. Overcoming this problem would help users to access lower-cost, more affordable, loans and other financial services. TrustScore provides an opportunity to address this through recording users' trustworthiness, reflected in their participation in saving-circles.TrustScore's benefits are for all UK users of saving-circles.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
国内基金
海外基金
深度学习视角的FinTech风险知识获取与平台治理模型
-
批准号:71871172
-
项目类别:面上项目
-
资助金额:48.0万元
-
批准年份:2018
-
负责人:夏火松
-
依托单位: