First, data systems may not be equipped to handle the expanding scope of ESG data collection. This creates added complexity for FSIs that are already struggling with collating the data necessary for regulatory, management and financial reporting. Addressing the challenges of fragmented data sources, siloed processes and systems for data collection and reporting will be vital to deliver complete and accurate ESG disclosures and reporting. In addition, data used to support ESG related decisions being inherently non-financial may have historically been subject to weaker controls making them more vulnerable.
Second, existing data management capabilities of FSIs may not be sufficient to measure, value the impact of, and take strategic action on ESG metrics and concerns around environmental and social risks. For instance, applying data analytics to inform decision making on products that aid in financing climate outcomes. Having sufficient quality and the necessary data available is required to measure, track, and generate valuable ESG insights for internal and external stakeholders.
Third, existing data sets in FSIs are yet to be sufficient to understand, identify or measure the ESG risks in portfolios. Externally available proprietary licensed data sets can often be incomplete, lack robustness and the required specificity. Emerging technologies providing new levels of data (e.g. daily satellite imagery) are vast and often unstructured datasets which contain pertinent information, but extracting it is complex and fundamentally different to traditional financial data.
Are you interested to know more about ESG data risks? Watch this space for our next blog on "What are the risks IF FSI's don't get their ESG data right"