According to recent industry reports, 156 mn. of Indians who comprise the \u2018urban mass\u2019 and urban middle\u2019 section representing an annual income of USD 3000 and above have the potential of mass adoption of consumer credit. Of this the \u2018urban mass\u2019 constituting approximately 129 mn. have been mostly deprived of credit due to lack of credit history.<\/p>\n
Addressing this major concern, CASHe, India\u2019s leading digital lending company, promoted by serial entrepreneur and private equity investor V Raman Kumar, on Wednesday announced the launch of India\u2019s first alternate credit rating system \u2013 \u2018The Social Loan Quotient\u2019\u00a0(SLQ).<\/p>\n
India\u2019s first social behaviour-based credit-rating system, SLQ is a fast, unique and a path-breaking real time platform which leverages big data analytics, artificial intelligence and predictive tools. The innovative platform will help score millions of Indians, who otherwise have been left in the lurch for lack of consumer credit in the absence of credit history.<\/p>\n
Considering the young urban mass prefer to avail small ticket loans for short term, the existing traditional lending platforms such as banks and NBFCs\u2019 find it unviable to serve the segment. In addition, the lack of credit history further dampens the situation. Here SLQ will play a pivotal role in helping this large untapped population to avail credit on the basis of the score generated by the system. Soon, the platform will also be set open to other institutions (banks, NBFCs\u2019 and credit bureaus) to integrate and avail the system thereby helping them reach out to the masses.<\/p>\n
Unlike conventional lending agencies who rely only on an applicant\u2019s past financial transactions, CASHe\u2019s revolutionary approach links multiple online and offline data points like his mobile, social and media footprint, education, remuneration, career and financial history to calculate the borrower\u2019s credit score.<\/p>\n
There are millions across the country who\u00a0have never obtained a bank loan, however, they are internet users who shop on line, have a good social media presence, have a stable residential status and also have been using their mobile phones actively. SLQ will now use these factors or data points into consideration when assessing a customer\u2019s creditworthiness. The platform will analyze unstructured data from various sources \u2013 social media profiles, mobile data, KYC documents \u2013 to provide the users with a system that will instantaneously and continuously update a borrower\u2019s credit worthiness and insure sound underwriting.<\/p>\n
The scores are generated in\u00a0real time\u00a0and will enable the customer to know, within a few seconds,\u00a0if he qualifies for a loan with CASHe or not. Subsequently, on completion of the loan application process, every customer\u2019s personal SLQ score will now be displayed to him. This will provide the user with a reliable tool for accessing his\/her creditworthiness.<\/p>\n","protected":false},"excerpt":{"rendered":"
According to recent industry reports, 156 mn. of Indians who comprise the \u2018urban mass\u2019 and urban middle\u2019 section representing an annual income of USD 3000 and above have the potential of mass adoption of consumer credit. Of this the \u2018urban mass\u2019 constituting approximately 129 mn. have been mostly deprived of credit due to lack of […]<\/p>\n","protected":false},"author":3,"featured_media":1225,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[31],"tags":[579,581,580],"class_list":["post-1221","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-indias-first-alternate-credit-rating-system","tag-kyc","tag-the-social-loan-quotient-slq"],"aioseo_notices":[],"yoast_head":"\n