{"id":245,"date":"2021-08-28T21:52:50","date_gmt":"2021-08-29T01:52:50","guid":{"rendered":"http:\/\/blogs.bu.edu\/suchi\/?page_id=245"},"modified":"2026-02-18T19:22:59","modified_gmt":"2026-02-19T00:22:59","slug":"esgmateriality","status":"publish","type":"page","link":"https:\/\/blogs.bu.edu\/suchi\/esgmateriality\/","title":{"rendered":"ESG Materiality"},"content":{"rendered":"<p>My ESG research is funded by Boston University research Ignition grant (2020-21).<a href=\"https:\/\/www.esganalytics.ai\/\">\u00a0ESGAnalytics.Ai uses big data analytics and AI to map ESG materiality with\u00a0smart risk analytics<\/a>. ESGAnalytics.Ai Platform featured in The<a href=\"https:\/\/www.forrester.com\/report\/the-forrester-new-wave-climate-risk-analytics-q3-2020\/RES157308?objectid=RES157308\">\u00a0Forrester New WaveTM: Climate Risk Analytics, Q3 2020<\/a>. Our positioning in advanced analytics ranked the highest in the report.<\/p>\n<p>ESGAnalytics.Ai applies cutting-edge data analysis and machine learning approaches to help solve ESG data metrics, risk profiling, portfolio optimization based on ESG themes. We collect both structured and unstructured data (social media) to go beyond simple metrics in our ESG analytics suite for easy access via our SaaS platform. We eliminate data challenges and integrate data that reside in many data silos into one platform and apply AI algorithms to derive predictive business insights in the context of short-term and long-term climate, employment, economic and social, and other trends. Our unique \u201cbig data\u201d approach results in improved risk metrics, quantification of fuzzy ESG themes, and maintaining a competitive edge. We avoid\u00a0greenwashing ESG. Our data products are backed by robust scientific R&amp;D.<\/p>\n<p>Look at <a href=\"https:\/\/floodlightglobal.com\/\">FloodlightGlobal.com<\/a> for newer revisions and updates on my earlier ESG work<\/p>\n","protected":false},"excerpt":{"rendered":"<p>My ESG research is funded by Boston University research Ignition grant (2020-21).\u00a0ESGAnalytics.Ai uses big data analytics and AI to map ESG materiality with\u00a0smart risk analytics. ESGAnalytics.Ai Platform featured in The\u00a0Forrester New WaveTM: Climate Risk Analytics, Q3 2020. Our positioning in advanced analytics ranked the highest in the report. ESGAnalytics.Ai applies cutting-edge data analysis and machine &hellip; <a href=\"https:\/\/blogs.bu.edu\/suchi\/esgmateriality\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;ESG Materiality&#8221;<\/span><\/a><\/p>\n","protected":false},"author":2207,"featured_media":0,"parent":0,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/pages\/245"}],"collection":[{"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/users\/2207"}],"replies":[{"embeddable":true,"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/comments?post=245"}],"version-history":[{"count":7,"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/pages\/245\/revisions"}],"predecessor-version":[{"id":354,"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/pages\/245\/revisions\/354"}],"wp:attachment":[{"href":"https:\/\/blogs.bu.edu\/suchi\/wp-json\/wp\/v2\/media?parent=245"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}