Applying geospatial data to your net zero journey

The growth in use and understanding of geospatial data has impacted the financial services industry in a variety of ways. What was once only available to a few governments and technology companies is rapidly becoming the norm, with the geospatial data market forecast to grow to over $100bn by 2026 from $60bn today. Whilst there is clearly an investment opportunity, this growth should also drive more accurate environmental, social and governance (ESG) data and, ultimately, better informed ESG investing. This is especially true in markets and sectors where disclosures, and therefore data coverage, is low such as private equity and real estate.

The market is driven by new artificial intelligence and machine learning based geographic information system (GIS) solutions, development of smart cities and the urbanisation and increased deployment of remote sensors. But how can financial services firms make use of this data and inform their pathway to net zero?

Geospatial data can be an enabler to support transition journeys

Geospatial data can play a significant role in

• reimagining the “E”
• revitalising the “S” and
• restructuring the “G”

and therefore, transforming risks into opportunities.

Reimagining the “E”

With the Taskforce on Nature-related Financial Disclosures (TNFD) reporting on the horizon, biodiversity impacts of organisations will need to be quantified and understood. This includes the ability to calculate and reference-point methane emissions, measuring soil organic carbon through ground displacement, measuring or verifying carbon sequestration of nature-based solutions, measuring water stress and proximity to biodiverse areas.

Revitalising the “S”

Satellite imaging unlocks a new dimension to collecting human centred earth observation data at scale and speed, in areas not previously possible. It does this by helping define corporate social responsibility (CSR) strategies for organisations through identifying local areas at danger of transport anxiety and poverty; and identifying remote locations in need of banking services, potentially also highlighting vulnerable customers, forming part of Consumer Duty requirements. Geospatial data is the key that unlocks CSR locally and globally.

Restructuring the “G”

For organisations evaluating potential merger and acquisition (M&A) opportunities, but are unsure of the strength or accuracy of the subsidiary’s reporting, point methane emissions offer a different lens on company reported emissions data, allowing organisations to cut through potential greenwashing. Whilst industries are catching up with their transitioning process, financial services will need to put together the right resources to effectively support this journey.

Uses of geospatial data

A number of key characteristics are driving the increased use of geospatial data. With satellite imaging, multiple spectrums of data can be layered on top of one another improving accuracy versus air and ground surveys which are purely visual. Additional insights can be drawn from the ability to verify carbon credits, perhaps utilising spatial data geofencing to apply virtual perimeters to physical areas of land, allowing financial services firms to leverage offsets more transparently. This could lead to more meaningful conversations and support the delivery of transition plans. The ability of geospatial data models to provide forecasting also allows for better risk profile estimation and accurate depictions of carbon credit life cycles.

Furthermore, an increased number of specialised vendors in this space lowers costs, increases real-time data availability and improves timeliness when compared with company reported data. Active green investors, or those marketing sustainable funds need reliable and timely information to avoid any future risk of greenwashing or reputational damages.

Challenges with using geospatial data

Using geospatial data comes with its own set of challenges. As a relatively new data type, it requires the right operating model and upskilling of individuals to analyse and interpret the data. Existing architecture may need to be adapted or upgraded to take new types of data files (e.g., shape files). With large volumes this may impact storage and while third party software could be utilised to circumvent this, additional governance over data or reporting that is brought into the business may be necessary.

Whilst significantly cheaper and with the ability to gain additional insights via layering of multiple spectrums for example, free satellite data does come at a lower resolution (around 10m2) when compared with air drone data (around3cm2), so may not be the most appropriate source for certain use cases where image quality is a priority. Finally, with it being a relatively new data type, there is a degree of interpretation to results at this stage, however standardisation and normalisation is a consistent challenge across other types of ESG data.

How?EY teams can help

As space tech matures and the use for its invaluable insights across the financial services landscape, there is a need for a trusted team to navigate this complicated, complex, and sophisticated landscape.

Having worked with multiple clients across industries to pilot this journey EY teams understand its challenges both at a strategic level and at a day-to-day operational level. Using our business experience, regulatory insights, technical excellence, and subject matter knowledge on ESG we have developed multiple tools, accelerators, and data products to make this journey feel less daunting.

This article was co-authored by Jo Freeman-Young and Stuart Wallace . Please reach out to either of us to discuss any of the challenges you are currently facing.

The views reflected in this article are the views of the author and do not necessarily reflect the views of the global EY organisation or its member firms.