Big four major banks half-year results 2026

AI agents: from theory to value

Over the last two years, banks have moved rapidly from experimenting with AI to identifying the most valuable areas across the organisation to deploy it. As AI becomes a key enabler of growth strategies, the demand for team members with experience building, deploying, governing and realising the value of AI has risen, with key team members directly involved in scaling AI within banks taking advantage of their unique skills and moving between banks more frequently. 

AI talent is only one component of the workforce considerations related to AI, with banks increasing their deployment of AI-powered tools to enable team members to access and interact with data in new ways. The rapid rise of AI agents suggests that age of human–agent collaboration is near, with expectation that AI agents will take lead roles in managing projects in addition to peer-to-peer collaboration with their human colleagues. 

Access to talent is only one factor holding organisations back – KPMG’s global AI Pulse Q1 2026 found that data privacy, cyber security, quality of data, regulatory uncertainty and lack of risk management processes or governance present the greatest barriers to success. Trusted AI governance has become a differentiating factor as the banks seek to ensure that they are scaling AI whilst ensuring that the right frameworks, controls and guardrails are in place to build confidence with customers, shareholders and regulators.

Riding the regulatory wave in banking

CPS 230 operational risk and resilience regulation has now been live for the best part of a year, and organisations should have made material steps to reduce the risk of potential harm to their customers and the market they operate in. Whilst banks spent much of their time focused on compliance, management should have embedded governance and processes to allow them to more proactively manage operational risk, with the outcome of that being operational resilience.

Banks should be able to demonstrate comprehensive visibility of those operations that are genuinely critical to their customers and market, at a depth where they can balance investment decisions between commercial considerations and pre-emptive or corrective actions to prevent harm. 

This is simply good for business. Providing a recognised resilient service to your customers is an investment, not a compliance cost.

At the more exciting end of risk management, banks are rapidly spearheading a range of AI use cases to support risk and compliance management. These are aimed at increasing capacity to allow their people to focus on more valuable activity; or increasing effectiveness of the risk activities themselves (analysing issues and incidents). This innovation will continue at pace – although our view is that many of these are very much in pilot or proof-of-concept phase and not yet in a production phase.

But the potentials are enormous. Our Global Head of Risk Transformation recently visited and relayed that one global bank had surfaced well over 1,000 use cases. The question is not where the value is, but how to unlock it; and importantly, how does this change the profile of your risk professionals.

Financial crime: a smarter threat demanding smarter defences from banks

Financial crime remains one of the most significant risks facing banks, financial institutions, and the global economy. As criminal networks become more sophisticated, the role of financial institutions has never been more critical in preventing, detecting, and deterring illicit activity.

A major challenge lies in striking the right balance – meeting ever-tightening regulatory demands and managing the rising costs of compliance, while continuing to deliver seamless customer experiences, drive innovation, and maintain operational efficiency. It’s a complex environment, but getting financial crime compliance wrong is simply not an option.

To stay ahead, banks must evolve beyond traditional methods and legacy technology. Embracing modern, AI, intelligent, and data-driven solutions is key to achieving more effective, efficient, and dynamic onboarding, detection, and prevention – protecting not just institutions, but the integrity of the global financial system.

Cyber security priorities in evolving threat landscape for banks

For major banks, realising value from sustained cyber security investment is no longer just about deploying more technology. It requires continuously proving that people, platforms, and operating models are being optimised to materially reduce risk in a threat landscape that is evolving faster than ever.

While cyber security remains a board-level priority, CISOs are operating under increasing financial pressure. Economic headwinds are driving flatter budgets at the same time as attackers become more sophisticated. In many institutions, funding is being reallocated toward innovation – particularly AI and automation – forcing CISOs to make sharper, more strategic investment decisions that anticipate risk rather than simply react to incidents.

AI now sits at the centre of this tension. On one hand, generative AI and machine learning are powerful defensive force multipliers, enabling faster detection, automated response, and improved analyst productivity. On the other, the same technologies are being weaponised by adversaries to scale phishing, automate reconnaissance, bypass controls, and exploit human trust with unprecedented speed and precision. Banks are no longer just defending systems; they are defending against AI-enabled opponents.

In this environment, a security conscious organisation is not optional. Secure by design principles must be embedded across products, processes, and culture, from AI model development and data pipelines through to identity, access, and operations. This is foundational to maintaining trust, resilience, and regulatory confidence. As disruption accelerates, banks that treat AI security as both a defensive capability and an attack surface will be the ones that stay ahead of the threat.

Payments as a strategic imperative 

Payments has fundamentally shifted from a reliable, back office ‘run the bank’ capability to a strategic control point for customer experience, trust, data advantage, and ecosystem relevance. With the highest volume and frequency of any banking interaction, payments generate unmatched customer and merchant data signals while carrying disproportionate exposure to fraud, scams, regulatory scrutiny, and operational risk. As competition intensifies and cost pressures persist, banks increasingly need payments to do more than process transactions; it must differentiate the proposition, protect customers, and enable new digital journeys at scale. For group executives and boards, this is no longer a technology discussion but a strategic priority with direct consequences for growth, return on equity, resilience, and long-term relevance.

The KPMG report Global insights into modernising payments highlights that the conversation has moved from rails modernisation to capability modernisation. Banks are upgrading infrastructure, but the differentiated value is being created through emerging tech plus partnerships and the gaps remain consistent: customer experience, security/compliance, data monetisation, tokenisation and AI. At the same time, competition is shifting from linear to multi-vector: card networks are extending beyond traditional rails into broader services; fintechs are embedding payments invisibly into journeys and capturing value without a direct bank relationship; and Big Tech are resetting expectations on speed, simplicity and experience. The customers will benchmark banks against the best digital experience anywhere, not peer institutions. Australia has made real progress (e.g. NPP, wallets, card platform investment), but the risk is clear: platform change is necessary but not sufficient. Without operating model alignment, real time decisioning, and the ability to orchestrate across rails and partners, modernisation delivers complexity, not competitive advantage.

Artificial intelligence is increasingly driving consequential shifts in the payments landscape, and the window for banks to act from a position of strength is narrowing. Leading players are already deploying AI at scale across fraud and scam prevention, authorisation decisioning, disputes, and customer servicing, unencumbered by the legacy data silos that constrain many banks. KPMG Payments Insights 2026  highlights a widening capability gap: 71% of retailers see growing demand for tokenised payments, yet only 46% of banks offer it, and 82% expect AI to process payments autonomously, positioning AI as both a cost and capability advantage. The risk for banks is not access to AI, but execution: without clean, governed, real-time payments data and orchestration, AI remains a set of disconnected point solutions rather than a structural advantage. An AI-ready payments foundation is therefore not optional; it is the prerequisite to lifting approval rates, reducing fraud and scams, and materially improving customer outcomes at scale.

The imperative for major bank executive teams is to reset the payments agenda, shifting decisively from platform replacement to capability-led transformation with measurable business outcomes. This requires extracting full value from prior modernisation investments; hard-wiring AI readiness into the payments data, controls, and real-time decisioning stack; repositioning the bank from a closed provider to an ecosystem orchestrator; and elevating fraud and scam prevention from an operational cost centre to a frontline strategic capability whilst modernising the underlying payments infrastructure built over decays. The institutions that act with intent and disciplined sequencing over the next 12–24 months will define the next generation of Australian payments. Those that default to further analysis will increasingly be forced to respond on someone else’s terms at higher cost and with diminishing strategic control.

Responding to uncertainty as credit conditions tighten

Major banks are increasingly signalling a more cautious outlook, with higher provisions and impairment charges reflecting growing macro uncertainty, geopolitical risks and emerging sector-specific stresses. While underlying asset quality remains broadly resilient, banks are closely monitoring in anticipation of a slower economy, higher cost pressures and potential credit deterioration. This shift is coinciding with a tightening in credit conditions, as lenders apply greater scrutiny to borrower quality, pricing and security, particularly for leveraged, cyclical and energy exposed businesses. The result is a more selective and conservative credit environment, with reduced availability of capital for marginal borrowers and heightened refinancing and liquidity pressure across parts of the market.