AI is being gradually adopted in banking to enhance everything from efficiency and fraud risk management to marketing and collections. Beyond these standard payments processes, leading players are also using AI to enhance environmental sustainability in payments – and to increase customer engagement. 

AI Enhances Payments Businesses in Multiple Contexts  

Businesses that are not considering sustainability as part of core AI infrastructure and expansion of technology strategies are at risk of hindering their own progress, AINews said. Failing to keep pace with sustainable practices can cause reputational damage, as organisations may be seen as behind the curve in an increasingly sustainability-focused world, alongside risking non-compliance with regulations. 

At a broad level, Payneteasy said, AI and machine learning are used to support the development of environmentally conscious payments. These technologies allow developers to optimise the payment process, thereby reducing energy consumption. One example is using AI to identify periods of peak energy consumption, as well as energy inefficiencies and wastage, so they can control their energy usage better and increase efficiency. 

For payments business units in financial institutions, platform provider Fondy said, the environmental benefits of streamlining payments go far beyond replacing paper, plastic, and precious metals used to produce coins with digital payments. Digital payments don’t require the production of cash, coins, or cheques, which saves natural resources such as trees, water, and metals. They thus have a lower environmental footprint compared to traditional payment methods because they require minimal resources and help reduce carbon emissions. SaaS platform owners in particular rely on data-driven solutions to build sustainable services that can improve customer service, reduce energy usage, cut carbon emissions, conserve resources, and minimise waste, while measuring performance on sustainability goals. 

Focusing on marketing, research by Iryna Bashynska of the University of Krakow in Poland showed that AI-driven personalisation in advertising can enable more targeted and effective communication, aligning consumer interests with environmentally conscious practices. With 80% of consumers globally concerned about the environment and factoring it into their decisions, using AI to target these customers can have an immense positive impact. Companies can use AI to analyse consumer data to understand preferences, behaviours, and patterns, which enables advertisers to craft personalised messages that resonate with individuals interested in sustainability and increase engagement. AI-powered algorithms help identify specific segments interested in sustainable products or practices, so advertisers can create targeted campaigns that align with customers’ values. AI algorithms can also suggest eco-friendly alternatives or products based on consumers’ past behaviours or preferences. Then, AI allows advertisers to track metrics such as engagement, conversions, and consumer behaviour. 

In ecommerce, 2Stallions observed, integrating into platforms enables brands to highlight sustainable products more effectively, which can generate an eco-friendly mindset among consumers. AI can curate selections that align with customers’ values, thus making environmentally sustainable shopping easier and more appealing. Additionally, machine learning algorithms can offer insights into consumer preferences based on past behaviours, suggesting products that align with an individual’s eco-friendly values and fostering empowerment that encourages consumers to opt for greener alternatives. 

Moneythor explained how tracking the carbon footprint using a pre-calculated CO2 weight based on each transaction category, such as clothing or dining, can be enhanced with the detection of merchant details such as green electricity providers or eco-friendly sustainable businesses. It is then further adjusted by individual lifestyle preferences assigned to each transaction. 

Payments Leaders are Using AI 

Payments businesses are using AI in multiple ways to make their operations more sustainable and engage customers more effectively. 

Starbucks, for example, uses AI in its payment processes to speed up and make ordering and paying more efficient. Fondy said the AI technology can help reduce the need for paper receipts, which results in an enormous saving on paper and the need to cut down trees. 

For ATMs, Paragon explained that their environmental impact can be significant due to their energy consumption and the production of paper receipts. Many new ATMs are being designed with energy-efficient technologies and limited paper transactions. Some are even solar-powered. Automation and virtualisation are also being used to optimise many of the processes required to test, authenticate, authorise, and settle payment transactions, improving productivity and reducing energy consumption. 

For corporate payments, Yokoy said, AI plays a transformative role in how finance leaders track, control, and forecast expenses and spending. AI-powered dashboards offer up-to-the-minute insights that help to ensure spend compliance as well as real-time budget tracking and expense categorisation. Beyond those standard uses of AI, some companies have turned to corporate card solutions that also support their sustainability targets. These solutions offer features such as carbon footprint tracking, vendor sustainability scoring, and paperless workflows to align spending with company values. Some providers even use minimalist card designs or digital-first solutions that align with ESG goals. 

While assessing the environmental impact of payments can be complex, Fondy said the Åland Index on Amazon Web Services provides an innovative way to calculate the carbon dioxide impact of certain purchases and transactions. The index uses a simple API that businesses can integrate into digital payment and banking services, delivering insights and information directly to customers. 

Genify similarly uses payment data to calculate the carbon footprint of individuals and businesses. Its AI models identify merchants and categorise transactions, ensuring precise carbon footprint values beyond traditional Merchant Category Code (MCC) methods. Its methodology relies on seven distinct approaches depending on the nature of the merchant or counterparty, for precise carbon footprint calculation. It utilises more than 40 sources for enhanced precision, surpassing the generic estimates typically made based on MCCs. 

While AI is clearly important to core payments activities, using AI to deliver green solutions and engage customers far better offers an opportunity to grow the payments business in new ways. 

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Author: Richard Hartung, Associate, Singapore, Payments Consulting Network 

An experienced professional with over 20 years of expertise in the payments and consumer financial services industry, specifically in the Asia Pacific region. He has held various key roles in organizations such as Citibank, Mastercard, and OCBC Bank, and has established consultancy firm Transcarta to assist financial services companies with strategy, operations improvement, and market research. 

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