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How Data Science Can Enable SFDR Reporting

Enabling SFDR reporting is an essential dimension of bringing societal impact to markets. At Clarity AI, we believe that good, clear governance can be built-in -- adhering to established regulatory requirements as well as pushing for even more advanced internal controls. This task may seem herculean; however, as with many other multi-dimensional tasks, technology can provide a streamlined solution.

In this paper, we provide specific examples of the merits of using data science to enable SFDR reporting. The paper is framed around three specific use cases leveraging different data science techniques, illustrated through SFDR requirements:

  1. How data science can improve reliability of reported data
  2. How machine learning can expand data coverage
  3. How natural language processing can inform metric development