{"title":"MiSA -一个帮助边缘社区的小额贷款服务系统","authors":"Y. Mahajan, D. Krishnaswamy, P. Chelliah","doi":"10.1109/SusTech47890.2020.9150502","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a distributed edge+cloud system to assist with microlending services to communities, with machine learning catered to that specific community. A combination of technologies including microservices-based architecture and blockchain technology coupled with machine learning is utilized to provide microfinancing services to help sustain businesses in a local community, and to enable the community to grow into a thriving economy. To minimize the widespread expressed risk, in our prototype, the prediction of whether a loan will default or not is based on the various decision-enabling parameters and on any available information about the borrowers' past transaction as well as aggregate metrics related to the community that the borrower resides in. The authors hope that the suggested distributed edge+cloud architecture in the paper can be leveraged for other emerging sustainable edge applications as well.","PeriodicalId":184112,"journal":{"name":"2020 IEEE Conference on Technologies for Sustainability (SusTech)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MiSA - A System for a Microlending Service to Assist Edge Communities\",\"authors\":\"Y. Mahajan, D. Krishnaswamy, P. Chelliah\",\"doi\":\"10.1109/SusTech47890.2020.9150502\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a distributed edge+cloud system to assist with microlending services to communities, with machine learning catered to that specific community. A combination of technologies including microservices-based architecture and blockchain technology coupled with machine learning is utilized to provide microfinancing services to help sustain businesses in a local community, and to enable the community to grow into a thriving economy. To minimize the widespread expressed risk, in our prototype, the prediction of whether a loan will default or not is based on the various decision-enabling parameters and on any available information about the borrowers' past transaction as well as aggregate metrics related to the community that the borrower resides in. The authors hope that the suggested distributed edge+cloud architecture in the paper can be leveraged for other emerging sustainable edge applications as well.\",\"PeriodicalId\":184112,\"journal\":{\"name\":\"2020 IEEE Conference on Technologies for Sustainability (SusTech)\",\"volume\":\"8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Conference on Technologies for Sustainability (SusTech)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SusTech47890.2020.9150502\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Conference on Technologies for Sustainability (SusTech)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SusTech47890.2020.9150502","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MiSA - A System for a Microlending Service to Assist Edge Communities
In this paper, we propose a distributed edge+cloud system to assist with microlending services to communities, with machine learning catered to that specific community. A combination of technologies including microservices-based architecture and blockchain technology coupled with machine learning is utilized to provide microfinancing services to help sustain businesses in a local community, and to enable the community to grow into a thriving economy. To minimize the widespread expressed risk, in our prototype, the prediction of whether a loan will default or not is based on the various decision-enabling parameters and on any available information about the borrowers' past transaction as well as aggregate metrics related to the community that the borrower resides in. The authors hope that the suggested distributed edge+cloud architecture in the paper can be leveraged for other emerging sustainable edge applications as well.