Banks looking to custom build their own environmental, social and corporate governance (ESG) solutions must determine which data sets to use as they build out their ESG platforms.

A wide range of datasets exists that measure ESG both broadly and minutely — so choosing the right dataset makes a difference. Global IT research consultants the Everest Group studied 18 ESG data and analytics technology providers and categorized the market data providers into the following three groups:

1. Major financial data and research providers. These include Bloomberg, SAP Global and the FDIC, which have lately begun to share their ESG data and analytics as an extension of their existing offerings.
2. ESG-exclusive data providers have offerings that range from data reports and competitive analysis to portfolio management advisory solutions. Sustainalytics, which Citizens deployed in its solution, and HIP Investors are examples.
3. Niche solution providers specialize in subsets of ESG data, such as real estate assets or gender diversity data. Equileap is an example of a niche data provider.

With so much data, banks can struggle with which datasets to utilize — and that’s just one challenge, Everest Group analyst Kriti Gupta told Bank Automation News.

“The biggest, biggest challenge to me is data … where to look for this data,” Gupta said. “Second is the quality of data. And then finally, how do I process that data? So that data challenge is inherent in this ecosystem.”

Artificial intelligence can help process and make sense of this unstructured data, which might require social media sentiment analysis and real-time analysis of controversies that arise in the press, added Kriti Seth, also an Everest Group analyst.

There are also company reports, public filings, nongovernmental organization data — but these are unstructured and thus can’t be managed by an average relational database. Such data also may require a cloud-based infrastructure to scale and provide the processing power needed to parse and analyze it, according to Mukund Rao, chief business officer for banking, financial services and insurance for IT services and outsourcing company Mindtree.

“AI-based technologies are currently being extensively used, primarily for sourcing the right amount of data,” Seth said. “Traditional data management systems cannot handle this amount of data and hence, these AI technologies are being extensively used to source the right amount of data from the right sources, and then build that analytics layer over it because, without deriving the correct value out of it, it is of no use.”