In the last ten years, the regulatory community has had its eyes on repairing the financial system, identifying loopholes and gaps to prevent another international banking crisis from happening. Amidst this, another crisis of a different nature began to blossom: the long-term challenge of ensuring climate resilience of the financial system and considerations on what planet we leave behind for generations to come.
The tempo of climate change is alarming. Whereas it may seem that this is a worn-out cliché, the issue itself is not. In October of 2018, William Nordhaus was awarded the Nobel Prize for Economics for work on economic modelling of climate change, recognizing the importance of interaction between climate change and human economic activities. By recognizing that climate change is no longer an economically overlooked topic raised by non-profit organisations and activists in obscurity, Nordhaus demonstrated that environmental issues extend beyond the private sector. As “climate change”, “sustainability” “ESG” lost the status of mere buzzwords, central banks realized that environmental issues need to be a core component of their decision-making. The motivation for this is not one-dimensional: central banks need to understand the impact of climate change on financial stability and monetary policy, support the green transition through their policies and assess how climate change impacts the financial sector. However, just as they shape their existing policies based on cold, harsh data provided by financial institutions, banks need to leverage data for effective green finance policies. Not only that, central banks need to shape these green policies based on a common understanding of the data that is given to them.
Source: OMFIF Analysis
Recognizing that the collection of environmental data is submerged in a “black box” of information asymmetry, environmental risk analysis is fraught with a shortage of data and data inconsistencies. Today, comparing environmental data that is provided by financial institutions is like comparing a green apple to a green pear: both are fruit, and both are green, but ultimately, they have a different shape and taste. To overcome this data asymmetry, central banks and regulators need to be able collect unified data. Financial institutions on the other hand, need to understand data requirements that are expected of them.
- What environmental data do I want to collect?
- How do I want to build relationships between different environmental data?
- What do I want to analyse from the data that is submitted to me?
Approaching the problem statement of the G20 TechSprint, we realised that embarking on a journey towards unified environmental data required a diverse team of business and data experts, analysts as well as specialists with a knowledge of legal requirements. But the Team still required one last member- the support of a solution to bind together the concept of combining legal requirements, classifications and data requirements.
