17 Nov

What COP26 Means for Financial Services and Why Data Is the Key to Net Zero

Sean Robertson

COP26 has drawn to a close.

And there have been a few key environment, social and corporate governance (ESG) announcements that will have significant consequences for financial services and insurance organisations (FSIs).

In this blog, I’d like to unpack some of these announcements, what they mean for FSIs and how they can take the first steps towards building out the kind of data programs and platforms that will support them in executing ESG initiatives.

COP26 Key Announcements

There are two key announcements that caught my attention.

1) Substantial climate funding from the financial sector

A group of 450 banks and insurers, going under the name of The Glasgow Financial Alliance for Net Zero (Gfanz), have committed $130 trillion of capital to tackle climate change between now and 2050.

That’s about 40% of the world's financial assets!

However, many commentators pointed out that a large part of this capital is stuck in property credit or still invested in the fossil-fuel eco-system, making it unclear how much of the $130 trillion can actually be invested in green projects.

2) The UK commits to becoming the world’s first net-zero financial centre

The Chancellor has committed to using the “historic” climate commitments from private companies to fund the net-zero transition, including the move away from coal, the shift to electric cars, and the planting of more trees.

What does this mean for FSIs?

There is significant work afoot for FSIs in the next few years in terms of becoming more sustainable and contributing to the net-zero target.

Most critically, the Chancellor has demanded FS institutions show how they are going to hit their targets by 2023.

They will be required to develop a transition plan that will set out how an organization will adapt as the world transitions towards a low-carbon economy.

It should set out:

1) High-level targets the organisation is using to mitigate climate risk

2) Interim milestones

3) Actionable steps the organisation plans to take to hit those targets

What would it take for the financial industry to meet this massive ask? The key themes have already been well-documented and are covered by the following three main categories:

1) Accelerate the speed of change through community and enterprise change

Climate change is not just an emissions issue, it is caused by overconsumption, inequality and biodiversity destruction.

Many areas will need to be addressed including energy efficiency, transport decarbonisation, new climate funding accelerators, carbon impact tracking, social change, sustainable supply chains, brand pressure etc.

2) Reducing the most harmful climate change-causing activities

The direct impact of CO2 and other harmful gases comes from the most harmful activities of hydrocarbon extraction and use.

Direct action to address this or influence transition is key to addressing this theme.

3) Embed ESG into organisational decision-making and risk assessment

Uncertainty in transition, physical, market and operational risk in property, environment and other affected  industries will need to be embedded into human and automated organisational decision-making.

4) Making operations ESG compliant and net zero

There are several key themes involved in becoming ESG compliant and reducing carbon emissions including renewable energy, transport decarbonisation, application and data centre optimisation and ethical supply chains.

The million-dollar question is: how can FSIs embed these actions into their operating models?

How Can FSIs Transition?

There are many areas in which FSIs can begin to make progress putting together and executing a vision for net-zero.

Risk and treasury departments have already started to include climate transition, physical and liability risk into their models.

Product teams will be developing ESG focused products in the investments space.

Marketing teams will be supplementing their marketing value chain across awareness, consideration, sale and retention with ESG content and campaigns.

Operations teams will be reviewing how their operations meet net zero targets. Their physical infrastructure and transport systems will need to be de-carbonised, while apps are migrated to the cloud (where possible).

But all of this is incredibly difficult work.

What is core to all of it, though, is data.

Why Data Is the Key to Transition

Core to all these usage patterns is that FSIs need to implement ESG data value chains.

These will be data processes and capabilities that constantly sense, integrate and analyse customer, operational and external data associated with ESG initiatives.

These data can then be integrated into their operational and commercial activities and platforms.

However, in my experience, of supporting a leading retail bank in building out an ESG data value chain and the underlying ESG intelligence platform, there are numerous challenges that present themselves:

  • Legacy technology: the legacy analytical ecosystem – where most of the data processing and analytics workloads still exist – can’t keep up with the demand or the changes needed for ESG requirements

  • Data scope and volume: many hundreds of internal and external data feeds both streaming and batch will need to be integrated over the next 12-18 months

  • Limits of existing op models: usage patterns demand flexibility and scalability, and a mix of pre-canned capabilities and as well as self service capabilities which is difficult to support with existing operational models

  • Flexible data models: new types of data models which span the entire organization but are also federated will be required as ESG affects all part of an organisation

  • AI and visualisation: new AI and visualisation labs will be required as this is a brand new field of research and development for end user consumption

  • Talent shortage: there is scarce technical resource in data to support this accelerated demand

What can FSIs do to meet these challenges?

To drive this initiative forward, FS organisations need to create a modern ESG intelligence hub in the cloud and put the right operational model around it:

  • Flexibility: develop a platform that can consume streaming and batch data internally and externally

  • On-demand capabilities: Self-service capabilities for data integration, data modelling and creation of new data products

  • Product development environments: build lab and development environments for visualisation, machine learning and product development which products can be taken from proof-of-concept all the way through to production

  • Modern data best practices: the platform should have all the traits of a modern data environment of security, access, privacy policy execution and leading data discovery and accessibility

  • Modern software development practices: include best practices from DevOps including agile development, automation and release management

What Support Is Available?

Our launch partners at Mesh-AI offer capabilities to support modern platforms and operating models to support ESG data initiatives.


Databricks provides a flexible modern data platform driven by notebooks which incorporate streaming and batch data, promote data to be operationally resilient and are machine learning ready. We’ve written elsewhere about why Databricks is such a big deal for the enterprise.

In a recent case study, for example, Databricks were able to support Standard and Poors (S&P) to leverage ESG data and artificial intelligence to help its customers make smarter socially responsible investments.

Databricks also have an ESG solution accelerator to quantify the holistic ESG impact of any investment.

The Public Cloud

AWS offers a comprehensive cloud platform across application, data, analytics and AI.  And has developed out significant platform and expertise for ESG labs and operational outcomes. You can check out some case studies here and here.

Azure also offers comprehensive cloud platform capabilities across application, data, analytics and AI, read a case study here.

Google which also has an extensive set of capabilities in applications, data, analytics and AI. You can read about Google’s region picker here, which includes data like carbon footprint and latency.

This year Google introduced a new tool leveraging that data –  a Google Cloud region picker that gives customers the ability to assess key inputs like price, latency to their end users and carbon footprint, as they choose which Google Cloud region to run in.

Final Thoughts 

There is no ESG data silver bullet.

However, a strategic and federated approach to ESG intelligence that addresses these challenges in small steps, in addition to adding modern fit-for-purpose data capabilities will help keep up with the demand.

Baseline, analyse, act and measure.

Repeat. Repeat. Repeat.

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