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by uma
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From 6 April 2022, more than 1,300 of the largest UK-registered companies and financial institutions will have to disclose climate-related financial information on a mandatory basis, in line with recommendations from the Task Force on Climate-Related Financial Disclosures (TCFD)*. This will include many of the UK’s largest traded companies, banks and insurers, as well as private companies with more than 500 employees and £500 million in turnover.

Mads Toubro, senior vice president, EMEA at Precisely, warns that businesses will need to fine-tune their data integrity models in order to comply with these new regulations and to be able to make strategic decisions based on their environmental, social, and governance (ESG) data:

“Companies have only days before these new regulations on disclosing climate-related financial information are enforced, and before their ESG reporting is put to the test on the public stage. For businesses to be compliant with these new regulations, they will need to understand what they must report, who owns the responsibility for the reporting, and where they can find the information. In other words, foundational elements of data integrity, such as the adoption of a robust data governance and quality framework, will be crucial for collecting the right data and actively monitoring and reporting on ESG initiatives.

“The problem for many organisations though, is that their ESG data does not have the right accuracy, consistency and context to able to report on it, let alone use it to make worthwhile changes regarding their ESG initiatives.

“In this era of rapidly advancing technology and growing need for transparent climate-related information, employing a data integrity strategy that includes an effective framework for data governance and quality serves a vital function within every organisation, regardless of size or industry. It enables businesses to make decisions based on trustworthy and transparent data and helps them understand, not only what their data assets are and how to access them, but also how to use that data most effectively. Additionally, it can maximise and quantify the value of data, by preserving its quality, measuring its worth, and maintaining consistency of usage across the entire enterprise. 

“Many data governance frameworks fail for two reasons: for being too complex or too time-consuming. However, successful data governance models are those that have organisational alignment, an enterprise-wide framework, clearly defined business requirements, and detailed objectives to achieve data understanding and trust.”