Good data is a prerequisite for robust ESG programs and creating new financial services in areas like banking, investing and lending. However, ESG data is often incomplete, inconsistent, out of date and spread across silos. There is no standard taxonomy for ESG data, making it hard to use.
We discuss:
- Why using only structured data is of limited value, but enhancing it with unstructured data can help you gain a comprehensive view
- How organizations can leverage unstructured data to derive ESG sentiments to differentiate their products and services
- How organizations can use ESG sentiments (signals and themes) to measure sustainability, integrate them into the risk assessment process, or evolve their brand.
Incorporating real-time unstructured data helps you adapt to a rapidly changing environment and empowers you to better manage your initiatives while delivering services that meet the growing demand for socially-responsible behavior.
