Central banks are searching for ways to streamline and optimise by leveraging innovation, including cloud technology, artificial intelligence and distributed-ledger technology.

Digital transformation is high on the strategic agenda for central banks. Amid a wave of innovation driven by cloud, artificial intelligence and digital assets, central authorities worldwide are looking to leverage new technologies and platforms to comprehensively optimise monetary operations and reserve management.

With the right solutions and infrastructure in place, central banks can realise new efficiencies, scale and agility to improve resilience and meet new market needs that maintain trust in their abilities and stewardship.

To meet modern demands, central banks need modern systems. Increasingly, these institutions are learning the importance of a cross-function, cross-asset platform to automate workflows and gain a centralised, real-time view of debt, liquidity and reserves with robust limit and compliance monitoring. 

Evolving operating models

Ensuring adequate foreign exchange reserves involves controlling liquidity, market and credit risks while managing asset allocation, currency composition and portfolio duration. Reserve managers’ strategies may consider external debt levels and test vulnerability to external shocks, as well as analyse interest rate shifts and changes in exchange rate dynamics.

Reserve management and market operations are structured differently across and within central banks. However, just like pioneering financial firms, financial and monetary authorities worldwide stand to benefit from operational optimisation through streamlined internal architectures, further enhanced by leveraging cloud technology and responsibly implementing AI.

Cloud-enabled analytics can inform reserve managers’ strategy reviews and portfolio-weighting adjustments to optimise returns and manage risks. Intraday and overnight repos may be seamlessly executed, supported by intelligence generated from scalable data lakes. AI can augment human decision-making across monetary operations and reserve management, and central banks are already testing and using it in their operations. 

AI adoption growing

Indeed, “AI and technology are becoming critical for optimising reserve management,” an official from a central bank in the Americas told Central Banking in response to the HSBC Trends in reserve management 2025 survey.

Among 84 central banks with over $7 trillion managed in FX reserves, 29% of reserve managers said they were considering using AI and 11% said it was already in use. Asked in 2024 about the potential of AI in reserve management, a resounding 93% of 88 reserve managers viewed it positively, agreeing that it can help optimise central banks’ portfolios in areas such as rebalancing strategies, tax efficiency and risk-adjusted returns.

Top areas identified for applying AI among 82 reserve managers were reporting (85%), trading and execution (71%), risk management (67%) and portfolio management (66%), followed by strategic asset allocation (59%) and cyber security (54%).

The Bank of Portugal’s Alya AI initiative exemplifies the power of AI insights in enabling proactive reserve management. Its market sentiment analysis function has helped the central bank diagnose market trends based on unstructured information pooled from news and research that can be turned into actionable intelligence.

However, there are signs there is a gap between technological ambition among central bank officials and their ability to implement cutting-edge solutions without public-private partnership.

The Central Banking 2025 Fintech benchmarks revealed just 5% of 20 central banks said they currently use the cloud for reserve management or market sentiment analysis. More broadly, although 80% of 30 central bank respondents said they use cloud services, only half of those use the cloud for AI tools (40%), and fewer still for its enhanced processing power (20%). Resources are a key issue, officials told the Central Banking Summer Meetings 2025. Beyond resources, other important considerations to adoption include platform capacity and implementation road maps.

Nevertheless, exclusive comments shared with Central Banking in the Fintech benchmarks revealed that the perceived advantages of cloud technology among central bankers include reduced IT costs and novel computing. “Upgrades and infrastructure management are easier and quicker,” said one official from a central bank in the Americas. “Scalability and cutting-edge technologies” are benefits, said another.

Risk management pertaining to upgrades is critical, and it is essential that the increased sophistication of analytical and operational capabilities is matched by the resilience of the new systems powering them. In this vein, business continuity also emerged as one of the greatest perceived benefits of cloud services (71%) among 28 central banks responding to the benchmarks. 

DLT offers new opportunities

Furthermore, as the new generation of money and digital assets is being built, a future-proof approach to technological transformation at central banks must also include the capacity to manage smart contracts on distributed-ledger technology (DLT) to invest in digital bonds and execute monetary and open market operations. This is the momentum of the market.

“We believe the next era of reserve and monetary policy management will be defined by agility, AI-powered platforms and secure, real-time digital infrastructure that streamlines and efficiently connects the financial ecosystem. Nasdaq is committed to partnering with central banks to deliver resilient, future-proof solutions that enable them to embrace innovation while safeguarding financial stability,” said Sophie Marnhier-Foy, Nasdaq vice-president and head of client solutions strategy, financial technology.

DLT has “emerged as a transformative force, reshaping industries and redefining traditional processes,” Arthur Yuen, deputy chief executive of the Hong Kong Monetary Authority, said in March 2025. “Its true potential lies not only in the technology itself but in the mindset with which it is approached.”

Meeting the moment, some central banks have already begun exploring conducting monetary operations on DLT. In June 2024, the Swiss National Bank (SNB), which holds more than $1 trillion in FX reserves, became the world’s first central bank to conduct a monetary policy operation on the promising new financial rails.

Like other central banks, to achieve its goal of price stability, the SNB sets interest on reserves and manages Swiss franc liquidity on the money market via liquidity-providing or liquidity-absorbing transactions. In this groundbreaking transaction, the central bank issued SNB bills settled in wholesale central bank digital currency at SDX, a regulated third-party digital exchange and distributed-ledger platform. Officials have said the SNB’s mission in this work is driven by the importance of being able to engage with new financial systems that may become systemically important.

Meanwhile, bond markets are also beginning to embrace digitally native bonds. In 2024, the Republic of Slovenia issued the first-ever sovereign digital bonds in the eurozone and in Europe, the Middle East and Africa, after earlier offerings by the World Bank and the European Investment Bank. The highly anticipated European Central Bank trials conducted throughout 2024 included intraday and overnight repo transactions using DLT. 

A platform to safeguard stability and embrace innovation

As change and innovation accelerate, central banks will feel more pressure to adapt. But digital transformation is an expansive, intensive effort, and central banks can benefit from efficient on-ramps to modernisation that provide automation, real-time data and analytics, and purpose-built tooling for optimised investment decisions, compliance and effective monetary policy measures powered by cloud, AI and DLT to unlock agility and efficiency.

For many central banks, the next step on their modernisation journies will be building AI-ready foundations combining traditional and digital assets in low-touch, automated and secure ecosystems.