Building the future of central banking by investing in people and technology

Today’s central banking landscape is defined by rapid technological advancement, rising emerging markets and growing complexity.

As the financial system becomes more interconnected and complex, central banks need agile systems that allow them to conduct operations in, and understand the dynamics of, the economic systems they oversee, while managing their own reserve portfolios.

Yet manual processes and workflows at central banks are expensive, time-consuming, prone to human error and thus to risk. Central bank modernisation is essential to ensure these vital institutions can meet the increasing demands of their mandates and prepare for future opportunities.

The growing importance of data management

The changing nature of financial risk management means central bank infrastructure must be able to handle ever-larger volumes of granular data efficiently: this is the foundation on which insights are generated and trusted operations depend.

Despite the vital role of data, exclusive Central Banking Fintech 2025 benchmarks data shows the current data landscape within central banks is highly siloed. Just half (50%) of 32 central banks said they have a centralised data collection centre, meaning different teams may request the same data and thus duplicate efforts processing it. Definitions of key measures may also differ between financial authorities within the same jurisdiction.

As settlement evolves from T+1 to instant, interoperable and immutable, data flows between financial entities are creating faster and more interconnected markets. As a result, central banks need to be technologically agile if they are to effectively understand and oversee these systems, building transparency and stability. This is achieved through robust, automated data management at financial authorities.

Central banks planning their modernisation journeys often prioritise data management at its core. A modular system approach means upgrades can be targeted and conducted without operational disruptions while advancing functionality to decipher and support tomorrow’s digital financial markets.

Critically, data is also the lifeblood of artificial intelligence. As well as the resource efficiencies and insights enabled by data standardisation and streamlined workflow operationalisation, sound data management is also essential for future-proofing central banks’ AI deployment. The Bank for International Settlements is clear that AI is both “poised to have a profound effect on the financial system and the real economy” and has “significant potential” to enhance central banks’ own policy analysis and execution.

Cloud as a modernisation lever

Cloud technology can be used as a strategic tool to maximise the benefits of new technology capabilities within central banks. Here, public-private partnerships are key. Central Banking’s exclusive benchmarking data also revealed that some 90% of central banks had their cloud services developed either exclusively by, or in collaboration with, a third party.

Investing in cloud technology to build out digital transformation means central banks can engage service providers to build new capacity out gradually, embodying a hybrid approach as manual processes become more automated.

As well as the resource efficiencies and insights enabled by data standardisation and streamlined workflow operationalisation, sound data management is also essential for future-proofing central banks’ AI deployment

Approaches to cloud technology system design by central banks vary in practice. Third-party providers fully manage the underlying infrastructure of public clouds, while private clouds have a dedicated infrastructure suited to sensitive data. The Fintech 2025 benchmarks data revealed that most central banks operate either public (47%) or hybrid public-private (47%) environments, where at least one cloud server is under the central bank’s direct control.

Cloud technology enables rapid experimentation with AI through model training, and deployment with the option of computational power that scales according to needs – thus enhancing cost savings.

Geographic access to cloud servers is more varied, with central banks taking domestic, overseas and hybrid strategies. Cloud technology systems can be tailored to each central bank’s security needs and domestic legislative requirements. Contracts with providers should also set out data governance across jurisdictions if located overseas.

Organisational strategy for change

Investment in technology is just one part of the digital transformation journey, however. Officials wishing to drive digital transformation in an era defined by rapid technological change will need the support of team members to bridge expertise from across their institutions. Many central banks are also engaging in international knowledge sharing to support their colleagues worldwide.

Central banks on a digital transformation journey often describe connecting top-down leadership with rigorous bottom-up testing through the establishment of interdisciplinary teams to drive their vision. This fosters collaboration, steers resource allocation and ensures robust IT and governance systems are put in place.

Cross-disciplinary teams may include stakeholders in departments that conduct operations and use data and analytics – as well as post-trade processing, risk management, legal and IT – to plan timelines and deliver updates. Moving from slow manual processes to streamlined workflows is important, but this must be finely balanced with risk management to ensure seamless operational continuity.

Training teams and investing in people is integral to implementing changes and driving continuous improvements, as stakeholders contribute to expanding the technology’s use cases and development. The use of AI could require additional staff training and audits, as laws worldwide move towards enshrining explainability and accountability standards.

Indeed, AI implementation starts with AI literacy for the team and the enforcement of defined guard-rails, as well as uncomplicated expected business and process key performance indicators. Guard-rails may include limits on use cases and a clear process for humans reviewing AI output to keep a human in the loop.

Optimising the modernisation journey

A strategic technology partner that invests in continuous innovation can reduce the overhead and talent resources required to experiment with, iterate and deploy AI.

With the benefit of cloud-enabled data frameworks and cloud services, a solution such as Nasdaq’s Calypso allows central banks to access innovation and implement it with minimal disruption. This allows institutions to focus on delivering their mandates and not the logistics and risk of digital transformation projects. At the same time, Calypso can be tailored to meet specific and evolving reserve management and market operation needs, as markets move towards tokenisation and the adoption of digital assets.

Technological upgrades focused on data mark the beginning of a digital transformation journey and AI adoption, not the end. Investment in staff is essential and partnerships with technology providers can be a powerful way for central banks to ensure they remain effective guardians of monetary and financial stability.

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