{"id":5927,"date":"2025-09-26T23:37:58","date_gmt":"2025-09-26T23:37:58","guid":{"rendered":"https:\/\/anbc.org.br\/?p=5927"},"modified":"2025-12-17T23:44:20","modified_gmt":"2025-12-17T23:44:20","slug":"artificial-intelligence-in-credit-from-promise-to-practice","status":"publish","type":"post","link":"https:\/\/anbc.org.br\/en\/inteligencia-artificial-no-credito-da-promessa-a-pratica\/","title":{"rendered":"Artificial Intelligence in Credit: from promise to practice"},"content":{"rendered":"<div class=\"article-main__content\" data-test-id=\"publishing-text-block\">\n<div class=\"article-main__content\" data-test-id=\"publishing-text-block\">\n<div class=\"article-main__content\" data-test-id=\"publishing-text-block\">\n<div class=\"article-main__content\" data-test-id=\"publishing-text-block\">\n<div class=\"article-main__content\" data-test-id=\"publishing-text-block\"><\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>Artificial Intelligence (AI) has been a concrete reality in the credit sector for over 20 years, with machine learning technology, for example. Today, with the expanded use of Generative AI, the sector is incorporating more and more innovations to generate value for companies, consumers and society.<\/p>\n<p>At ANBC, we are closely following this evolution. The AI journey in credit is already showing tangible results: reduced operating costs, increased predictive accuracy, improved consumer experience and expanded access to responsible credit.<\/p>\n<p>The application of AI in Brazilian bureaux has revolutionized processes such as:<\/p>\n<ul>\n<li>Immediate updating of the credit score, using alternative data and decisions in minutes.<\/li>\n<li>Real-time fraud detection, with machine learning analyzing behavioral patterns.<\/li>\n<li>Automation of statistical modeling, reducing costs by up to 66% and speeding up model development from weeks to days.<\/li>\n<\/ul>\n<p>These advances are not just technical, they have direct implications for financial inclusion, credit sustainability and data governance.<\/p>\n<h3>AI applied with concrete results in Brazilian credit bureaus<\/h3>\n<p>In Brazil, bureaus are investing heavily in AI to transform the credit market with security, speed and responsibility.<\/p>\n<p>In one of the companies, more than <strong>70% of the new models developed in 2023 incorporated machine learning and deep learning<\/strong>, and its cloud infrastructure:<\/p>\n<ul>\n<li>20x faster data processing<\/li>\n<li>Greater security for highly regulated data<\/li>\n<li>Agility in decision-making, with processes that used to take months being completed in days<\/li>\n<\/ul>\n<p>In this case, AI is combined with human evaluation to ensure contextualized and effective decisions, such as detecting financial anomalies and consumption patterns.<\/p>\n<p id=\"ember63\" class=\"ember-view reader-text-block__paragraph\">Another Brazilian bank has implemented <strong>instant write-off<\/strong>, allowing the <strong>credit score <\/strong>be<strong> updated in seconds<\/strong>. This allows consumers to pay off their debt and have immediate access to new credit conditions, generating a structural change in the market.<\/p>\n<p id=\"ember64\" class=\"ember-view reader-text-block__paragraph\">In addition, the incorporation of data from social programs, telcos and utilities into predictive models has contributed to <strong>reduce defaults by up to 15%<\/strong>, without affecting approval levels.<\/p>\n<p>Also on the national scene, the use of advanced analytical platforms has enabled a local bureau:<\/p>\n<ul>\n<li>Tripling the production of analytical models<\/li>\n<li>Reduce development time from 3-4 weeks to 2-5 days<\/li>\n<li>Increase the accuracy of the models by up to 8 points in the KS index, an indicator of predictive quality.<\/li>\n<\/ul>\n<p id=\"ember67\" class=\"ember-view reader-text-block__paragraph\">Another example of innovation in the sector is the use of models that analyze <strong>up to 24 months of account history<\/strong>, including actual payment amounts, to more accurately predict future consumer behavior.<\/p>\n<p id=\"ember68\" class=\"ember-view reader-text-block__paragraph\">These models offer:<\/p>\n<ul>\n<li>More than 300 premium predictive algorithms<\/li>\n<li>Analysis of payment behavior and balance magnitude<\/li>\n<\/ul>\n<p id=\"ember70\" class=\"ember-view reader-text-block__paragraph\">This granularity transforms credit decision-making, allowing for more personalized products, <strong>reducing defaults<\/strong> e <strong>responsible credit expansion<\/strong>.<\/p>\n<p id=\"ember71\" class=\"ember-view reader-text-block__paragraph\">AI governance is guided by ethical concepts within the bureaus, with extensive information security, monitored and transparent systems. Responsible innovation allows for increased efficiency and accuracy, fostering the inclusion and sustainability of credit in the country.<\/p>\n<h3>Regulation and responsibility: the role of ANBC<\/h3>\n<p>In addition to closely following national and international trends, ANBC has been active in debates on AI regulation, advocating a balanced approach that:<\/p>\n<ul>\n<li>Differentiate high-risk systems from traditional credit models.<\/li>\n<li>Avoid excessive interpretations of discrimination, in line with the LGPD.<\/li>\n<li>Promote decentralized governance and proportional penalties.<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<p><span style=\"color: #222222; font-family: Montserrat, sans-serif; font-weight: bold; letter-spacing: -0.025rem;\">Thanks for reading! Access other content at<\/span><a style=\"font-family: Montserrat, sans-serif; font-weight: bold; letter-spacing: -0.025rem;\" href=\"https:\/\/www.linkedin.com\/company\/anbc-associa%C3%A7%C3%A3o-nacional-dos-bir%C3%B4s-de-cr%C3%A9dito\" target=\"_blank\" rel=\"noopener\">\u00a0ANBC website<\/a><span style=\"color: #222222; font-family: Montserrat, sans-serif; font-weight: bold; letter-spacing: -0.025rem;\">.<\/span><\/p>\n<div class=\"article-main__content\" data-test-id=\"publishing-text-block\">\n<p>&nbsp;<\/p>\n<h3 class=\"h3-xl\" style=\"text-align: center;\"><img loading=\"lazy\" decoding=\"async\" class=\"alignleft size-full wp-image-1261\" style=\"font-size: 1rem; color: #333333; font-family: Roboto, 'Helvetica Neue', Helvetica, Arial, sans-serif; font-weight: 300;\" src=\"http:\/\/anbc.org.br\/wp-content\/uploads\/2023\/12\/elias-sfeir.webp\" alt=\"elias sfeir\" width=\"100\" height=\"100\" \/><\/h3>\n<p>&nbsp;<\/p>\n<h6>President of ANBC - National Association of Credit Bureaus. Representative of Latin America in the World Bank Credit Committee. He also represents Brazil and Latin America in credit organisations accross the world, such as ACCIS, BIIA and ALACRED.<\/h6>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>A Intelig\u00eancia Artificial (IA) \u00e9 uma realidade concreta no setor de cr\u00e9dito h\u00e1 mais de 20 anos, com tecnologia de machine learning, por exemplo. Atualmente, com a amplia\u00e7\u00e3o de uso da IA Generativa, o setor est\u00e1 incorporando cada vez mais&#8230;<\/p>","protected":false},"author":1,"featured_media":5928,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_seopress_robots_primary_cat":"none","_seopress_titles_title":"Intelig\u00eancia Artificial no Cr\u00e9dito: da promessa \u00e0 pr\u00e1tica","_seopress_titles_desc":"A Intelig\u00eancia Artificial (IA) \u00e9 uma realidade concreta no setor de cr\u00e9dito h\u00e1 mais de 20 anos, com tecnologia de machine learning, por exemplo","_seopress_robots_index":"","pgc_sgb_lightbox_settings":"","footnotes":""},"categories":[46],"tags":[779],"class_list":["post-5927","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog","tag-inteligencia-artificial-no-credito","blog-post"],"_links":{"self":[{"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/posts\/5927","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/comments?post=5927"}],"version-history":[{"count":1,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/posts\/5927\/revisions"}],"predecessor-version":[{"id":5929,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/posts\/5927\/revisions\/5929"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/media\/5928"}],"wp:attachment":[{"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/media?parent=5927"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/categories?post=5927"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/anbc.org.br\/en\/wp-json\/wp\/v2\/tags?post=5927"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}