As global leaders gather this week at COP26 in Glasgow, one of their top goals is to mobilize finance to secure net zero emissions and keep 1.5 degrees warming within reach. To do this, COP26 leaders are challenging all financial stakeholders to take climate into account in every financial decision.
Technology is playing a vital role in this effort. I have a background in financial services and fintech, and work in Google Cloud’s CTO Office with technology leaders across financial services and other industries to transform sustainability in their organizations. Here are three technology areas that I think are vital for sustainable finance, both to manage climate-related risks and to enable new climate finance opportunities.
Understanding localized climate risks
COP26 leaders are calling on companies to be transparent about the risks inherent in climate change. Every business will be affected by a warming planet, and it’s critical to understand precisely how these events will affect company operations, employees’ lives, and entire value chains. As BlackRock’s CEO Larry Fink has stated, climate risk is investment risk.
However, physical risks from climate change are not evenly distributed around the world. Some areas will see increased floods, and others will face droughts or wildfires. Rising sea levels will affect coastal areas and severe winter storms will affect places with historically milder winters.
Geospatial analytics and modeling has the potential to give us a much more accurate view of these localized climate-related physical risks. The Task Force on Climate-Related Financial Disclosures (TCFD) recommends factoring the geographic location of the organization’s value chain (both upstream and downstream), as well as the organization’s own assets, into any climate change scenario analysis efforts. Using tools like Google Earth Engine and BigQuery, it’s possible to create a localized, precise understanding of climate-related physical risks for each location in the value chain.
Using AI to improve climate disclosure
Another key finance priority for COP26 is improving the quantity, quality and comparability of climate-related disclosures by companies, so that investors and regulators can better understand climate risks and opportunities. To date, most of this disclosure has been published as human-readable documents. One example is Google’s Environmental Report. These documents are very helpful if you’re in a position to deeply study an individual company, but what if you want a broad view of sustainability progress across markets?
This is where AI comes in. Specifically, natural language machine learning approaches can be applied to classifying and extracting structured information from sustainability disclosures. The TCFD recently used an AI approach to quantify the level of sustainability disclosure across 1,701 companies from 69 countries. A team of experts manually labeled text passages in a sample of 150 documents, assigning a “yes” or “no” value to each review question, such as “does the company disclose Scope 1, Scope 2, and, if appropriate, Scope 3 greenhouse gas emissions?”. Then they trained a model with these labels and used it to predict yes/no responses for the entire corpus. The resulting analytics were used by the task force to assess the state of adoption and level of disclosures.
Investors, regulators, and companies can all benefit from adopting natural language AI techniques to better understand sustainability documents, whether those are from suppliers, investors, customers, or even competitors. Tools like Google Document AI and Vertex AutoML can accelerate AI adoption in these organizations.
Collaborative sustainability data sharing
COP26 is demonstrating the power of collaboration to solve climate challenges. It’s clear that individual organizations cannot go at this alone; everyone must work together! In the financial world, companies need to share information with investors, suppliers need to share data with companies, and everyone needs to share data with regulators and central banks.
In an enterprise setting, sharing data can be difficult, involving legacy tools, slow cycle times, and one-way processes. What if sharing climate and sustainability data were as simple as sharing photos or documents in the cloud? Cloud-native tools like Analytics Hub, built on BigQuery, can definitely help here.
As a bonus, thanks to Google’s renewable energy matching, building these solutions on Google Cloud today means the net operational greenhouse gas emissions associated with your application is zero. And over time, the gross carbon footprint of these workloads will decrease as we make progress towards our goal of running on carbon-free energy around the clock by 2030.
This article originally appeared in the Google Cloud Blog.
Jeff Sternberg 