{"id":14233,"date":"2023-10-26T10:32:47","date_gmt":"2023-10-26T10:32:47","guid":{"rendered":"https:\/\/www.esgtoday.com\/?p=14233"},"modified":"2023-10-26T10:32:48","modified_gmt":"2023-10-26T10:32:48","slug":"bloomberg-launches-indicators-to-measure-exposure-to-physical-climate-risk","status":"publish","type":"post","link":"https:\/\/www.esgtoday.com\/bloomberg-launches-indicators-to-measure-exposure-to-physical-climate-risk\/","title":{"rendered":"Bloomberg Launches Indicators to Measure Exposure to Physical Climate Risk"},"content":{"rendered":"\n
\n <\/div>\n\n\n\n

Business and financial markets information service provider Bloomberg and climate financial risk data analytics provider Riskthinking.AI announced today the launch of new science-based physical risk indicators, aimed at enabling companies and investors to assess and understand exposure to climate-related risks such as floods, droughts and wildfires.<\/p>\n\n\n\n

According to the companies, the launch of the new indicators comes as regulators are moving to require disclosure of climate-related risks, in new and emerging reporting regimes including Europe\u2019s CSRD and the new international IFRS sustainability disclosure standards, and as measuring exposure to extreme weather events is becoming increasingly to important to investors as well.<\/p>\n\n\n\n

The new physical risk indicators are the first to account for every climate scenario endorsed by the Intergovernmental Panel on Climate Change (IPCC), the UN body for assessing the science related to climate change, according to the companies, enabling an approach that accounts for numerous possible future outcomes, including tail risk events.<\/p>\n\n\n\n

The indicators combine Bloomberg\u2019s data on more than 1 million physical assets \u2013 such as manufacturing sites, energy plants, mining operations, office buildings, and retail sites \u2013 across nearly 50,000 companies, with Riskthinking.AI\u2019s granular dataset of global climate change projections and proprietary methodology to calculate companies\u2019 physical risk exposure level. The methodology enables users to drill down to the individual assets of a parent company to analyze specific threats, and combined with Bloomberg’s global supply chain data, the indicators also help reveal physical vulnerabilities of key suppliers.<\/p>\n\n\n\n

The solution also provides access to the documentation detailing the underlying calculations for reporting on climate-related risks, in line with the CSRD, the recommendations of the TCFD and the IFRS Sustainability Disclosure Standards.<\/p>\n\n\n\n

Riskthinking.AI CEO and Founder Dr. Ron Dembo said:<\/p>\n\n\n\n

\n

\u201cOur pioneering methodology enables investors to use the uncertainty inherent in climate modeling as a strength to support better investment decisions. We don’t rely on a single model or scenario when managing risks or defining a strategy. Our outputs consider climate projections from 51 leading climate research centers and universities to capture a broad range of possible future outcomes.\u201d<\/p>\n<\/blockquote>\n\n\n\n

The launch of the new indicators follows Bloomberg\u2019s equity investment last year in Riskthinking.AI, and the formation of a partnership to explore the use of advanced risk modelling techniques in providing a deeper view into the climate-related impacts on the financial system.<\/p>\n\n\n\n

Patricia Torres, Global Head of Sustainable Finance Solutions at Bloomberg, said:<\/p>\n\n\n\n

\n

“Achieving reliable assessment of exposure to physical hazards relies on large amounts of geospatial and climate data to effectively account for the uncertainty inherent in future projections. By bringing together cutting-edge climate science with investor grade physical assets data, we can help investors and companies to better navigate the increasingly complex financial and regulatory environment regarding physical risk.”<\/p>\n<\/blockquote>\n\n\n\n

The new indicators are available on the Bloomberg Terminal and via Bloomberg Data License.<\/p><\/span>","protected":false},"excerpt":{"rendered":"

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