Over one billion people around the world are unbanked, according to the World Bank Group’s Financial Inclusion Overview. That’s one-eighth of the global population. For these individuals, financial inclusion is more than just access to banking – the World Bank identifies it as a “catalyst” for seven of the 17 United Nations Sustainable Development Goals as it “fosters economic growth and employment, economic empowerment of women and contributes to eliminating poverty”. Accelerating equality was a key takeaway from the group’s 2024 annual meeting. As financial institutions work to expand access to their services, technology – particularly AI – is emerging as a powerful tool to drive inclusion and support responsible growth.
“Financial inclusion is an important part of every institution’s strategy,” says Peter Hazou, director of business development for worldwide financial services at Microsoft. “It can open doors to new and underserved markets. Across banking, capital markets and insurance there are opportunities to expand existing products and solutions to new, traditionally marginalised groups. This represents a sustainable opening for firms while expanding economic opportunity equitably.”
Financial inclusion can be a “catalyst” for seven of the 17 United Nations Sustainable Development Goals
A mortgage lender, for example, could translate its forms into other languages to increase accessibility for marginalised groups and use a multi-language chatbot to provide them with support throughout the process.
“For a long time, we’ve had AI tooling in the form of machine learning, which is good at dealing with quantitative information, but enabling financial literacy is a conversation and happens in the qualitative realm,” says Hazou. “With natural language generative AI capabilities, financial literacy can be fostered through new agentic experiences and a single chatbot interface.
“However, it is important to recognise that financial inclusion requires programmatic and well-governed strategies to understand the use cases and investments needed to bring them to life. When it comes to AI-enabled financial inclusion, governance processes will be crucial in ensuring fairness, accessibility and the application of domain expertise when serving diverse communities.”
Microsoft’s Matthew Sekol (left) and Peter Hazou
Microsoft’s AI technology is enabling financial institutions to make their services accessible to more customers. For example, credit risk company Trusting Social is using Microsoft Azure services to reach unbanked individuals in Asia. The firm first partnered with Microsoft to build its data foundation using Azure Kubernetes Services, Database for PostgreSQL and Databricks. Next, it used Azure Synapse Analytics to unify insights in its data warehouse and leveraged autonomous AI-powered agents in Azure Agent Foundry to boost customer acquisition in emerging markets and among underbanked consumers.
“By leveraging cloud technologies, stringent governance models and AI, Trusting Social was able to tune its credit scoring model with a new e-Know Your Customer solution and build agents to provide a personalised experience for customers at scale,” says Hazou.
Trusting Social is using AI-powered agents in Azure Agent Foundry to reach unbanked individuals
Increasing financial inclusion is just one small part of the industry’s broader environmental, social and governance (ESG) efforts. While banks and insurance firms are not the heaviest users of environmental assets themselves, according to the World Economic Forum, they do finance projects and companies that are.
“Financial services firms sit at a unique intersection of ESG because they have their internal operational metrics, as every company does, but they also provide capital or insure projects and assets for other companies,” says Matthew Sekol, sustainability global black belt at Microsoft. “As a result, they have a broad value chain that they can have varying levels of influence over. We’ve seen a mix of regulatory pushes globally from a disclosure perspective, and also governments building programmes to support a sustainable transition, often involving partnerships with lenders.”
Any company approaching an ESG initiative should first focus on the ESG factors that are most relevant and impactful to their business, stakeholders and industry. For financial services firms, this could mean prioritising areas such as climate risk and sustainable investing, diversity, equity and inclusion, and regulatory compliance. Once these priorities have been established, the focus can then switch to what the data says about those areas.
“The firm must lead with how their functions intersect with ESG topics to help identify risks and opportunities, otherwise they may find themselves in over their heads on efforts they cannot sustain,” explains Sekol. “The starting point for use cases is the data, yet we can’t be so mired in it that we don’t act,” says Sekol. “Data is critical to making an informed decision and ESG represents new data points that firms may be unfamiliar with. When used to drive a compelling use case, data is the proof to trace through to success.”
Financial services providers might interpret data differently depending on their unique risks and opportunities.
“A bank may plan for a percentage of loans to be aligned with a sustainable transition, meaning the metrics would be found in the lending portfolio and may collect borrower data like financed projects’ goals rather than internal metrics,” says Sekol. “For insurance, they may not be as focused on operational reductions and instead want to ensure that the companies and communities they support are building in climate resilience and adaptation planning. The data points here would be acute and chronic climate risk and adaptation efforts that can be taken, rather than mitigation efforts. Across the whole financial services industry though, the data to showcase ESG efforts will largely come from the credit or investment vehicles used but be supported by metrics outside of the company.”
Measuring growth is a key step towards sustainability goals, risk management and opportunity creation. But much of the material data that banks are working with will come from outside their company.
“Data, technical debt and a complex but necessary regulatory environment are some of the challenges that surface when a bank attempts to integrate something new like an ESG data set and perspective,” says Sekol. “Historically, these challenges have been met with point solutions like purpose-built data lakes. For example, an ESG analyst would ask for access to the loan book, a data lake would be created with just the information needed, and the analyst would add in relevant ESG metrics to create a risk score.
“However, this only adds another challenge as a lack of data centralisation, endless data copies and poor governance models lead to the creation of outdated data swamps. Following the example, the ESG analyst might be missing critical datapoints or may be using outdated information to deliver that score!”
Bringing together the firm’s internal and external datasets requires eliminating technical debt with a data lakehouse. Microsoft Fabric is built around this idea with solutions including Azure Synapse Analytics, Azure Data Factory and Power BI to connect data from multiple sources.
“Fabric brings together data tooling, storage, data science tooling, governance controls and a cybersecurity plane so that a company can work from one copy of the data, ensuring it is consistent, clean and controlled,” says Sekol.
While no data modernisation is a small undertaking, data lakehouses powered by Fabric aim to ease the pain of upgrading data systems so that banks can integrate AI into their business.
“Financial services firms are finding that there is a lot of value to be had in the data when they start digging,” says Sekol. “Some of this is coming from the firm’s sustainability office. For example, the process to collect data to support its goals involves going around to the firm’s functions, gathering activity data and calculating it into ESG metrics. Some sustainability offices also integrate into the credit, lending or insurance lines of business, providing unique insights.”
As a result, the sustainability office sees everything the firm does, recognising the value they can provide if they could democratise the data and opening up the conversations to do just that.
“While the reporting has been the focus over the past few years, this new data trend to support insights around risks and opportunities is nascent,” concludes Sekol. “It moves beyond the goals into integrating ESG information into the firm’s decision-making as another data point.”
Partner perspectives
We asked Microsoft partners LSEG and Melissa how they are helping financial services firms achieve their sustainability goals
“We are partnering with Microsoft to help financial services firms through co-developing new cloud data and modelling services using Azure services and LSEG’s advanced data modelling and analytics capabilities,” says Emily Prince, group head of analytics at LSEG. “We provide optionality for financial institutions to move towards less carbon-intensive operations in the cloud, enabling businesses to scale efficiently without the need for complicated processes and systems that often require extra servers – as well as providing best-in-class data and analytics to inform investment decisions that incorporate sustainability principles at their core.”
“Every year, six million trees and more than 300 million pounds of paper are wasted on undeliverable mail,” says Greg Brown, vice president of marketing at Melissa. “Melissa’s Microsoft-powered solutions for address verification and change-of-address help financial services firms keep their address data clean, accurate and up to date.”
Read more from these partners in the Spring 2025 issue of Technology Record. Don’t miss out – subscribe for free today and get future issues delivered straight to your inbox.