“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
• 金额: $ 25.41万
• 依托单位: BLOOM GROUP HOLDING LTD
• 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
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10052433
• 关键词: TrustScore; fintech; machine; learning; growing

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.

排除金融服务的损失，英国数百万的生活。它损害了英国的经济：创造金融保障，发育迟缓的企业家主义，增加失业，社会保障和医疗保健成本。信用评级是财务包含的关键障碍。克服此问题将帮助用户访问低成本，更实惠的贷款和其他金融服务。 TrustScore提供了一个通过记录用户的信任度来解决此问题的机会，这反映在他们参与Saving-Circles中。TrustScore的好处适用于所有保存圆形的英国用户。