{"id":8010,"date":"2018-01-11T08:44:42","date_gmt":"2018-01-11T08:44:42","guid":{"rendered":"http:\/\/bulletins.bfconsulting.com\/?p=8010"},"modified":"2018-01-16T12:48:00","modified_gmt":"2018-01-16T12:48:00","slug":"big-data-uses-in-financial-institutions","status":"publish","type":"post","link":"https:\/\/bulletins.bfconsulting.com\/en\/big-data-uses-in-financial-institutions\/","title":{"rendered":"Big Data uses in financial institutions"},"content":{"rendered":"<p>The usefulness of Big Data and how this type of analytics can be deployed in financial institutions is only starting to be understood in Kazakhstan. Specifically, there are a number of projects being implemented in the country to study how a number of indicators from various data sources affect financial discipline. For example, a testing phase in being concluded which aims to correlate data from mobile carriers with a borrower\u2019s fulfillment of his\/her repayment obligations. Similar projects in Russia have resulted in an increase of 5-7% in the effectiveness of credit scoring. Social scoring (obtaining data from social media websites such as Facebook and Vkontakte) and psychometric scoring (based on responses to specially formulated questions) are also being studied for their potential to enhance credit scoring.<\/p>\n<div class=\"rpbt_shortcode\">\n\n<div id='rpbt-related-gallery-1' class='gallery related-gallery related-galleryid-8010 gallery-columns-3 gallery-size-thumbnail'><figure class='gallery-item' role='group' aria-label='BFC FinTech Monitor 9th \u2013 19th October'>\n\t\t\t<div class='gallery-icon landscape'>\n\t\t\t\t<a href='https:\/\/bulletins.bfconsulting.com\/en\/bfc-fintech-monitor-9th-19th-october\/'><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/bulletins.bfconsulting.com\/wp-content\/uploads\/2020\/10\/4af1a697-7fd6-4a93-b2b3-8254fb513eaa1-150x150.png\" class=\"attachment-thumbnail size-thumbnail\" alt=\"\" aria-describedby=\"rpbt-related-gallery-1-15427\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='rpbt-related-gallery-1-15427'>\n\t\t\t\tBFC FinTech Monitor 9th \u2013 19th October\n\t\t\t\t<\/figcaption><\/figure><figure class='gallery-item' role='group' aria-label='Number of cyberattacks on Kazakh banks increasing'>\n\t\t\t<div class='gallery-icon landscape'>\n\t\t\t\t<a href='https:\/\/bulletins.bfconsulting.com\/en\/number-of-cyberattacks-on-kazakh-banks-increasing\/'><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/bulletins.bfconsulting.com\/wp-content\/uploads\/2018\/10\/number-of-cyberattacks-on-kazakh-banks-increasing-150x150.png\" class=\"attachment-thumbnail size-thumbnail\" alt=\"\" aria-describedby=\"rpbt-related-gallery-1-11230\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='rpbt-related-gallery-1-11230'>\n\t\t\t\tNumber of cyberattacks on Kazakh banks increasing\n\t\t\t\t<\/figcaption><\/figure><figure class='gallery-item' role='group' aria-label='Payme application launches online loans in Uzbekistan'>\n\t\t\t<div class='gallery-icon landscape'>\n\t\t\t\t<a href='https:\/\/bulletins.bfconsulting.com\/en\/payme-application-launches-online-loans-in-uzbekistan\/'><img loading=\"lazy\" decoding=\"async\" width=\"150\" height=\"150\" src=\"https:\/\/bulletins.bfconsulting.com\/wp-content\/uploads\/2018\/05\/online-payment-design_23-2147697568-1-150x150.jpg\" class=\"attachment-thumbnail size-thumbnail\" alt=\"\" aria-describedby=\"rpbt-related-gallery-1-9872\" \/><\/a>\n\t\t\t<\/div>\n\t\t\t\t<figcaption class='wp-caption-text gallery-caption' id='rpbt-related-gallery-1-9872'>\n\t\t\t\tPayme application launches online loans in Uzbekistan\n\t\t\t\t<\/figcaption><\/figure>\n\t\t<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>The usefulness of Big Data and how this type of analytics can be deployed in financial institutions is only starting to be understood in Kazakhstan. Specifically, there are a number of projects being implemented in the country to study how a number of indicators from various data sources affect financial discipline. For example, a testing &hellip;<\/p>\n","protected":false},"author":5,"featured_media":8011,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10,76],"tags":[80,196,197],"class_list":["post-8010","post","type-post","status-publish","format-standard","has-post-thumbnail","","category-fintech","category-kazakhstan","tag-artificial-intelligence","tag-credit-scoring","tag-data","b_post_type-regional-fintech-news"],"_links":{"self":[{"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/posts\/8010","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/comments?post=8010"}],"version-history":[{"count":3,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/posts\/8010\/revisions"}],"predecessor-version":[{"id":8179,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/posts\/8010\/revisions\/8179"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/media\/8011"}],"wp:attachment":[{"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/media?parent=8010"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/categories?post=8010"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bulletins.bfconsulting.com\/en\/wp-json\/wp\/v2\/tags?post=8010"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}