The Glasgow Financial Alliance for Net Zero (GFANZ) was one of the significant outcomes of the recent COP26 Climate Conference. As The Guardian Newspaper
said at the time “Finance is the key to the massive economic transformation required to move away from fossil fuels and reach net zero so the global economy can be run without damaging the climate.”
However, as many other commentators have stated, signing up to agreements is easy – implementing them is hard. This is where the impetus for action must now come. But how do global financial institutions pivot their decision making to focus both investment and lending on net-zero goals? Data lies at the heart of this new green decision making, and banks must develop ‘green data brains
’ to help them change how they do business.
Allow Data to Flow
What are the practical steps that banks can take to implement these commitments, and what role will data play? Immediately it is clear to see that banks will need to consider a much wider set of factors when considering in which project to invest, or to which customer to lend. As well as due diligence on risk and regulatory compliance around AML and KYC factors, they will now have to have detailed information on the environmental impact of a customer’s activities, and the proposed impact of any customer project they fund. This will entail integration of potentially hundreds of new sources of information, from macro climate change data to the micro detail of carbon emissions from specific operations. Much of this data will come from the customers themselves or in many segments or geographies, 3rd
parties. Not all this new data will be entirely reliable or accurate and most of it will be in different formats.
McKinsey now see net zero as "an organizing principle for business"
. GFANZ is where this principle becomes reality as to meet their commitments, banks need to interrogate data at a much finer granularity. Aggregate or average emissions data at an industry or sector level will no longer be enough to underpin real business decision making.
To be able to be audited, and justify lending and investment decisions, banks will need emissions data on specific projects, individual buildings, or even particular farm fields. Meeting this requirement will not be easy. They need to plan now to create the enterprise data platforms that can allow data at scale, with variety and granularity to flow across the whole bank. Manual, Excel-based, analysis will not scale to these levels, nor will discrete department or function-centric tactical solutions. Strategic data infrastructure coupled with automation is the only option to cope with the quantities of data that needs to flow into banks’ decision making.
The analytics, models, machine-learning, and AI solutions needed to deliver green investments and lending decisions all require an abundance of data. Banks need to act now to put these data foundations in place.
Avoid Islands of Data
Commitments like GFANZ, combined with increasingly demanding regulatory expectations, mean that sustainability data will need to influence virtually every decision across the bank. Preparing for this demands a centralised platform approach rather than the creation of new islands of data that support single decision-making functions. Data on the environmental impact of investments, the activities of customers, and even the bank’s own performance will need to flow across the enterprise so that it can support each and every decision. Teradata has shown with its Vantage solution that it has the platform that can scale to manage these critical data across even in the largest financial institutions.
But this is not an initiative that remains fully within the boundaries of the enterprise. The data institutions need to make effective sustainability decisions will come from multiple external sources. Some will be familiar to them, some less so. In addition, some data will come from customers and partners. It is likely to accelerate the adoption of Open Banking and the creation of numerous specialist data providers. These providers will acquire and supply data and could provide additional services as banks look to deliver on environmental commitments.
Innovations including greenhouse gas emissions dashboards, may present new opportunities for forward thinking banks to both meet their commitment and deliver helpful services to customers. To maximise the value of these 3rd
party contributors, banks will need to rely on enterprise data platforms that can provide and consume data. They will also need to support the efficient deployment of a wide range of analytical models leveraging diverse data to be used across the enterprise.
Establishing this frictionless flow of data between functions, internal and external suppliers and consumers is the foundation of the green brain necessary to implement sustainability commitments. As I’ll explore in the next blog, it is also the foundation of growth and new business for those banks that can get it right.
Start Preparing an Enterprise-Wide Data Platform
Commitments have been made, the world is looking on and time is short. Mandatory regulation is already in place to ensure that the industry really does ensure “every financial decision takes climate change into account,” as Mark Carney put it. Aside from the regulatory risk, reputational damage to those banks that fail, or are seen to fail, to play their part in the decarbonisation of the global economy, should be all the impetus needed to act now.
Effective data acquisition, storage and use will be critical to making the right decisions and showing how and why you made them. Now is the time to start building the enterprise-wide data platforms that will ensure all this new data is available when and where its needed. Talk to Teradata’s consultants
to explore how existing infrastructure can be leveraged and what new capabilities need to be introduced to make this a reality.
Simon Axon leads the Financial Services Industry Consulting practice in EMEA. His role is to help our customers drive more commercial value from their data by understanding the impact of integrated data and advanced analytics. Prior to taking up his current role, Simon led the Data Science, Business Analysis & Industry Consultancy practices in the UK & Ireland, utilising his diverse experience across multiple industries to understand our customer’s business and identify opportunities to leverage data and analytics to achieve high-impact business outcomes. Before joining Teradata in 2015, Simon worked for the Sainsbury's Group and CACI Limited.
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