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The key IT trends shaping financial services software in 2026 are AI moving toward wider use, modernization of legacy platforms and data foundations, stronger cybersecurity and resilience, and continued investment in payments, fraud prevention, and digital customer experience. These priorities depend on one another: AI and new customer features are difficult to scale when data is unreliable, systems do not integrate, or security and governance are inadequate.
What do the 2026 survey numbers actually show?
The figures below come from different studies and populations. They are useful signals of priorities, not a single, comparable forecast for every bank or financial institution.
| Finding | What it measures | Source and scope |
|---|---|---|
| 89% identified as innovators or fast followers | How respondents characterized their approach to technology change | KPMG’s 2026 global financial-services technology survey summary, covering 760 technology leaders |
| More than half said foundational technologies such as data, cloud, and cybersecurity deliver the majority of digital value | Respondents’ view of where digital value comes from; KPMG’s summary does not give an exact percentage | KPMG’s 2026 global financial-services technology survey summary, covering 760 technology leaders |
| 87% planned modernization investment in the next 12 months | Planned investment, not completed spending | Finastra’s 2026 State of the Nation Survey; research conducted in November 2025 among 1,509 managers and executives across 11 regions |
| 54% used fintech-provider partnerships as their default modernization approach | Reported approach to modernization, not evidence that partnerships are best for every institution | Finastra’s 2026 State of the Nation Survey; the same November 2025 population and scope |
| 29% prioritized cloud adoption | A stated investment priority | Finastra’s 2026 State of the Nation Survey; the same November 2025 population and scope |
| 96% were using, piloting, or planning to use AI; 61% said they had improved AI capabilities over the prior year | AI activity and reported capability improvement. The 96% figure does not mean all respondents had AI in production | Finastra’s 2026 State of the Nation Survey; the same November 2025 population and scope |
| 40% projected an increase in security investment in 2026 | A survey projection, not a measured increase in realized spending | Finastra’s 2026 State of the Nation Survey; the same November 2025 population and scope |
| More than 18,000 DORA-related incident reports through March 2026 | Reports received in the EU regulatory context, not a count of global incidents | European Banking Authority, June 2026 Risk Assessment Report |
Why is financial-services AI moving from trials toward wider use?
Institutions are exploring AI across payments, lending, compliance, and customer engagement. The next challenge is not simply acquiring models: it is deciding where AI belongs in a process, connecting it to reliable information and existing systems, and keeping its use accountable as it changes.
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Governance is also developing alongside deployment. The Financial Stability Board’s 10 June 2026 consultation report proposes 12 sound practices for organization-wide AI governance and management across the AI lifecycle. These are proposed practices in a consultation report, not binding rules.
What institutions need to settle before scaling
- Use case and accountability: Identify the business process, the human or team accountable for outcomes, and where human review or escalation is needed.
- Data readiness: Check whether information is accurate, appropriately governed, accessible to the system, and suitable for the intended use.
- System integration: Map how model inputs and outputs connect to core platforms, operational workflows, and customer-facing channels.
- Risk controls: Establish oversight across the lifecycle, including how performance, failures, and changes will be handled.
- Operating capacity: Provide the skills and infrastructure to run, monitor, and improve the capability after a pilot.
Why are modernization and data foundations still central?
Modernization is not a separate housekeeping project: it supports resilience, customer experience, payments capabilities, and the ability to apply AI in real workflows. Finastra’s survey connects modernization investment with these aims and identifies cloud adoption as one of the stated priorities. KPMG’s global financial-services summary likewise points to data, cybersecurity, infrastructure, skills, and governance as foundations for durable value, while identifying technical debt and talent shortages as execution constraints.
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For banks, integration is a particularly practical obstacle. KPMG’s 2026 Banking Technology Survey summary identifies integration with existing systems and processes as the leading stated barrier to AI deployment, followed by regulatory, legal, and ethical uncertainty, then poor data quality or readiness. That ordering is a reminder that a new application or model may add little value if the surrounding systems and information are not prepared to support it.
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There is no single architecture that fits every institution. Before choosing whether to modernize in place, replace a core platform, or work with a fintech provider, compare the options against the same operational questions:
| Decision lens | Questions to answer |
|---|---|
| Integration burden | Which existing systems, processes, and interfaces must remain connected during and after implementation? |
| Data quality and readiness | Can the approach work with current data, or must data ownership, quality, and architecture change first? |
| Security and resilience | How will the change affect cyber controls, service continuity, dependencies, and recovery arrangements? |
| Governance and regulatory fit | Can the institution maintain oversight, accountability, and evidence appropriate to the use and jurisdiction? |
| Use-case support | Does the option support the intended AI, payments, fraud-prevention, or customer-experience needs? |
| People and operating capacity | Does the institution have the skills and capacity to implement, operate, and govern the result? |
Finastra’s finding that 54% of its respondents used fintech partnerships as their default modernization approach describes a survey preference, not a universal prescription. Partnership, internal development, and platform replacement each need to be assessed against the institution’s integration, risk, and operating requirements.
How are cybersecurity and resilience shaping software choices?
Security and operational resilience are baseline requirements for financial software, not add-ons to be addressed after deployment. The Federal Reserve’s Cybersecurity and Financial System Resilience Report covers its cyber-risk policies and activities as well as current and emerging threats, including malware and supply-chain risks. The report index was last updated on 4 September 2026.
The European Banking Authority’s June 2026 risk assessment discusses system failures, cyber incidents, third-party dependencies, and risks associated with AI. Its figure of more than 18,000 DORA-related incident reports refers to reports received through March 2026 in the EU context; it should not be read as a global incident total.
Controls to include in implementation planning
- Assess third-party and supply-chain dependencies, including the services a new platform relies on.
- Define how the institution will monitor availability, detect incidents, and recover essential services.
- Include cyber risk and resilience requirements in architecture and procurement decisions, not only in final testing.
- For AI-enabled workflows, include governance and monitoring in the operating model rather than treating approval as a one-time launch gate.
Where do payments, fraud prevention, and customer experience fit?
These are investment priorities in their own right and practical tests of whether modernization delivers useful outcomes. KPMG’s 2026 Banking Technology Survey summary lists data-driven insights, cybersecurity, fraud prevention, digital customer experience, enterprise transformation, and data modernization among banking investment priorities. It also identifies payments as an area of pressure and future capability development.
Finastra’s survey identifies customer service and personalized experiences as prominent customer demands. Taken together, the priorities point to software that can support dependable transactions and relevant service while helping institutions manage fraud and risk. A technology program should therefore be assessed against the customer and operational process it is intended to improve, not just the number of new features it adds.
How should leaders turn these trends into an investment plan?
- Start with the business and risk outcome. Define the customer, operational, resilience, or control problem before selecting a technology.
- Map dependencies. Document the systems, data, workflows, and external providers the change depends on.
- Establish readiness. Identify gaps in data quality, integration, security, governance, skills, and operating capacity that could prevent adoption.
- Choose a delivery path. Compare modernization in place, platform replacement, and partnership using consistent criteria rather than assuming a single route is right for all needs.
- Plan for operation, not just launch. Assign ownership for oversight, resilience, incident handling, and ongoing improvement.
- Measure the intended result. Track whether the change improves the targeted process or service while meeting the institution’s risk and reliability requirements.
The survey figures are snapshots of stated priorities, plans, and self-reported activity. KPMG’s global technology-leader survey, its banking survey summary, and Finastra’s multi-region survey do not share one sample or scope. They indicate that institutions are pursuing change, but do not establish a universal adoption rate, spending outcome, or causal effect.
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