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“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
–TrustScore – 金融科技机器学习:通过储蓄俱乐部的既定做法建立信用档案,使服务不足的社区获得主流金融服务,从而发展英国经济
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 --

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中文摘要
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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.
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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: