69 points of view from our industry teams — filter by industry or topic, or search. Figures in each article are sourced or labelled.
Generative AI assistants made individual bankers faster. Agents that execute whole workflows under human supervision are what move the cost base — and they need a different operating model to do it safely.
2026 is the year programmable money moved from pilots to live value: real-value cross-border trials among central banks, bank deposit tokens on public chains and a US stablecoin law about to bite. Banks need a position on all three forms of money, not a bet on one.
The open-source record shows where AI in financial services is really being built: agent frameworks and finance reference agents, data connectors, and a thin but important layer of governance. Stars are loud; the signals that matter for banks are quieter.
Open models, agent frameworks and MCP connectors are now part of almost every bank’s AI stack. The licence, supply-chain and regulatory questions they raise are answerable — but only if intake is designed for AI, not just for software.
The easing cycle is over almost before it finished, and rates are rising again. The lesson of the past three years is that margin is now earned customer by customer, and that the primary relationship is the only deposit franchise worth defending.
Voluntary alliances have dissolved and US supervisors have stepped back, yet European and UK prudential expectations have hardened. For banks, climate is becoming a risk-management and data discipline rather than a public commitment, and financed-emissions data remain the weakest link.
Embedded finance keeps growing, but the US sponsor-bank enforcement wave showed that when a partnership fails, the bank's ledger and licence are what customers fall back on. The winners will be banks that can prove, every day, whose money is where.
Banks are more profitable than they have been in years, but their cost bases have hardly changed relative to assets. The next step change will come from redesigning work around AI, not from another round of cost containment.
Banks spend heavily on financial-crime compliance and still catch only a sliver of illicit flows. Agentic AI offers a different shape for the work — squads of narrow agents assembling evidence, with investigators making the call.
Banks earned more in 2025 than any industry on earth, yet investors still price them at the bottom of the league. The next leg of returns will come from productivity and precision, not balance-sheet heft.
Data-sharing regimes are widening from payment accounts to savings, pensions and insurance, but the rules are moving at very different speeds. The economics of access, not the APIs themselves, will decide who wins.
Finance teams still spend most of their time assembling numbers rather than explaining them. A continuous close, with agents reconciling and drafting commentary as transactions land, turns the finance function from reporter into navigator.
Card networks, big tech and standards bodies are building the rails for AI agents to transact on consumers' behalf. For banks, the shift rewrites the rules of authentication, liability, distribution and brand, and it is arriving faster than consumer trust.
Generative AI is shortening credit memos and cash-flow data is widening who can be scored. The rules on explaining and testing those decisions are shifting on both sides of the Atlantic, but the obligations have not gone away.
The rulebook is moving in two directions at once — EU deadlines deferred, US model-risk guidance rewritten, Asian supervisors naming AI agents explicitly. Banks that build one control framework for models and agents will not need to rebuild it for each regulator.
The UK's mandatory reimbursement regime is two years old, the EU has made payee verification universal for euro payments and Australia is legislating shared duties for banks, telcos and platforms. The evidence so far: shifting liability changes behaviour, but banks cannot stop scams alone.
Virtual assistants now handle a large share of routine banking conversations. The public record shows that the programmes that last are those that measure outcomes, not deflection, and make it easy to reach a person.
Payments revenue growth is slowing just as the rails underneath are being rebuilt. Instant account-to-account payments are becoming the default in much of Asia and Latin America, digital money is moving from trading to treasury, and banks must decide which layer they intend to own.
Models are no longer the constraint. Metadata, a shared semantic layer, knowledge graphs and lineage are — and banks that already invest in BCBS 239 compliance are closer to AI-ready data than they may think.
Instant payments are now mandatory across the euro area and growing fast in the US, and 2023 showed how quickly deposits can leave. Treasury needs a live view of intraday liquidity, and the data architecture to support it.
Southeast Asia has built some of the world's most advanced real-time and QR payment systems and licensed a new generation of digital banks. Payments have been won quickly; profitable lending has not. The next phase will be decided by data, credit and cost to serve, and incumbents still hold more cards than the headlines suggest.
Europe's Digital Operational Resilience Act has produced its first register of critical tech providers and its first year of incident data. With the UK's regime now live as well, the lesson is that resilience depends on third-party dependencies and system failures more than on dramatic cyberattacks.
Core replacement programmes have a long record of overruns and outages. A progressive path — data layer first, capabilities peeled off behind APIs and events, AI to read the legacy code — lowers the risk without lowering the ambition.
By the end of the decade the best banks will be felt more than seen: embedded in the journeys where customers live and work, run by humans supervising a digital workforce, and built on data they can trust. Here is the shape of that bank, and the operating model behind it.
The Bank of England, the ECB and the EBA are all reshaping how they collect data from banks. The banks that benefit will be the ones that pair common data definitions with traceable lineage and AI that interprets, reconciles and explains their returns.
The standards are published and the deadlines are converging on 2030–2035. For banks, post-quantum migration is a multi-year programme whose hardest first step is not cryptography at all: it is building a trustworthy inventory of every key, certificate and algorithm in the estate.