{"id":4799,"date":"2015-01-28T14:09:44","date_gmt":"2015-01-28T14:09:44","guid":{"rendered":"http:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=4799"},"modified":"2015-01-28T14:09:58","modified_gmt":"2015-01-28T14:09:58","slug":"banking-start-ups-adopt-new-tools-lending","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/banking-start-ups-adopt-new-tools-lending\/4799\/","title":{"rendered":"Banking Start-Ups Adopt New Tools for Lending"},"content":{"rendered":"SAN FRANCISCO \u2014 When bankers of the future decide whether to make a loan, they may look to see if potential customers use only capital letters when filling out forms, or at the amount of time they spend online reading terms and conditions \u2014 and not so much at credit history. These signals about behavior \u2014 picked up by sophisticated software that can scan thousands of pieces of data about online and offline lives \u2014 are the focus of a handful of start-ups that are creating new models of lending. No single signal is definitive, but each is <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/banking-start-ups-adopt-new-tools-lending\/4799\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>SAN FRANCISCO \u2014 When bankers of the future decide whether to make a loan, they may look to see if potential customers use only capital letters when filling out forms, or at the amount of time they spend online reading terms and conditions \u2014 and not so much at credit history. These signals about behavior [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11,48],"tags":[],"class_list":["post-4799","post","type-post","status-publish","format-standard","hentry","category-industry-news","category-left-hand"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/4799","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=4799"}],"version-history":[{"count":2,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/4799\/revisions"}],"predecessor-version":[{"id":4801,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/4799\/revisions\/4801"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=4799"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=4799"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=4799"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}