Bridging the ESG gap for banking operations (Steve Morgan)

Bridging the ESG gap for banking operations (Steve Morgan)

Bridging the ESG gap for banking operations (Steve Morgan) PlatoBlockchain Data Intelligence. Vertical Search. Ai.

Today, action on environmental, social, and governance (ESG) considerations can no longer be deprioritised when it comes to financial services. Banks in particular are under increased scrutiny to meet ESG targets from both a regulatory and reputational perspective, as well as to keep up with competitors in embedding ESG within the products they offer to consumers and businesses alike. Streamlining banking operations with intelligent automation will therefore be key in keeping banks ahead when it comes to risk management, moving forward with purpose and driving increased customer retention.

ESG reporting and the operations gap

Over the next few years banking stakeholders of all kinds – investors, employees, customers, governments, and beyond – are set to put a bigger emphasis on environmental, social, and corporate governance (ESG) reporting. Organisations that are perceived to be falling behind on ESG will struggle as more customers, and even employees, demand sustainable options. At the same time, climate change and extreme weather events will continue to cause significant impacts on bank customers, creating a need for more robust and predictive risk models and strategies. 

Concurrently, more stringent and extensive environmental regulations will necessitate shifts to more environmentally friendly solutions for banks and their customers by default. Such changes will benefit those that are already reducing their carbon impact and will push others to proactively anticipate emerging environmental regulations as a risk management strategy. If it hasn’t happened already, banks will have to reengineer data and operations architectures to focus on compliance and auditing capabilities that deliver greater accountability and traceability of decision-making – so getting ahead of this is key. 

Redefining operational backbones for ESG implementation

Embedding actions into core processes is where change can truly be sparked. When you consider lending, investments and savings, inflows to sustainable funds have increased rapidly from $5bn in 2018 to more than $70bn in 2021, with $120bn in new funds in the first half of 2022, according to Morningstar. Global sustainable assets hit the region of $2.5 trillion in December 2022 – a figure which is only likely to increase in the coming years.

For lending, many banks already have products in place on the corporate side such as green bonds, with lending rates reduced for improved environmental rating scores such as CO2 emission reduction. Banks are also moving into the retail space with green products such as green home loans where reduced rates are offered to housing with better energy efficiency ratings, or personal loans applied to solar panel installation or insulation improvements.

To keep ESG top-of-mind, banks need to redefine their operational backbones to build on existing technology investments whilst maintaining a future-focused edge. For example, to facilitate accessing, validating and managing internal and externally sourced ESG data, banks would do well to establish a centralised ESG data store. This allows the ability to efficiently manage multiple ESG data variables such as policies and frameworks, data management in its own right as well as running ESG data operations as appropriate. 

In particular, AI and intelligent automation are increasingly able to help banks keep themselves accountable to stringent ESG standards by improving the accuracy and efficiency of ESG reporting, reducing manual data entry errors and freeing up time for more in-depth analysis. Automated ESG reporting solutions are now becoming commonplace with AI-powered solutions such as Intelligent Document Processing (IDP) deployed to join up the dots when it comes to unstructured data points, as well as validating the data for reporting purposes. 

Increased implementation of such technologies will allow banking stakeholders to boost compliance efforts and adherence through more effectively monitoring and communicating ESG performance across departments, as well as linked to their suppliers. The goal should be to dramatically reduce duplicate requests and have fewer employees reading and responding to emails and instead processing answers – and remove much of the wall-to-wall manual processing that many will be used to when it comes to ESG.

Disrupted operations planning for greater ESG resiliency

The events of the last few years – and the pandemic in particular – have hammered the point home that banking operations models and resiliency frameworks need to be updated or reimagined to quickly adapt and succeed in the future. To drive effective movement on ESG priorities, banking operations decision makers need to understand how emerging ESG standards can be integrated into their existing workflows and processes to build more purpose-led companies. 

Today, this means having a disrupted operations playbook in mind which focuses on key priorities such as greater resiliency, not being so lean that it reduces the ability to adapt when there is a major change or disruption to operations, as well as balancing the need to automate with a customer experience that is still human and differentiated. To execute effectively on this, low-code solutions can provide banks with the ability to implement modernised, robust, and strategic business operations that can support distributed teams, adjust to shifting market conditions, and seamlessly reallocate work and resources based on changing demands.

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