At a Glance
Banks can baseline technology spend by separating run vs change costs and mapping them to regulatory obligations, platforms, and services, revealing structural inefficiencies and funding constraints to rebalance investment toward strategic modernization while maintaining compliance.
Why a spend baseline is a prerequisite for realistic strategy
In 2026, banking technology budgets are under simultaneous pressure: accelerate digital transformation, industrialize AI, strengthen cyber and resilience controls, and reduce the “high cost of low cost” created by legacy debt. A technology spend baseline turns these pressures into an objective reference point for executives. It clarifies how much capacity is truly available for change after non-discretionary obligations are funded, and it exposes where spend is being consumed by duplication, manual controls, and brittle platforms.
Without a baseline, strategy discussions often mix incompatible assumptions: boards approve change roadmaps without visibility into run obligations, while transformation programs understate the operating cost they will create (dual-running, new control requirements, and third-party dependencies). A baseline is therefore not a finance exercise; it is a governance tool for validating whether strategic ambitions are achievable with the bank’s current cost structure and delivery constraints.
What “baseline” looks like in 2026: the minimum metrics leaders need
A usable spend baseline is built from a small set of metrics that can be repeated quarter over quarter. The goal is comparability, not precision theater. Banks typically align baseline measures to spend totals, growth rates, workforce intensity, and category mix.
| Benchmark | 2026 reference point | How leaders use it |
|---|---|---|
| Total global retail banking IT spend | $307B (forecast) | Checks whether internal growth assumptions are aligned to market investment intensity |
| Average retail banking IT budget growth | ~6.3% (forecast) | Sets a reality check for “do more with less” plans when run obligations are rising |
| IT spend as % of revenue | Often cited around ~8% on average, with wide dispersion | Frames affordability and competitive intensity; highlights under- or over-investment risk |
| Technology cost as % of non-interest expense | Commonly referenced in the high teens to ~20% for retail banks | Supports cost-to-income discussions and identifies where tech cost is driving operating leverage |
| Tech spend per FTE (illustrative) | ~$35k | Indicates automation and platform efficiency, especially when volumes grow faster than cost |
| IT staff as % of total employees (illustrative) | >12% | Signals insourcing/outsourcing posture and whether delivery capacity is realistic for the roadmap |
Two cautions matter. First, benchmarks are not targets; they are comparators for decision-making. Second, the spread between institutions can be rational (business model, geography, risk profile), but only if leaders can explain the differences through documented choices and outcomes.
Run–Grow–Transform: the portfolio allocation baseline in 2026
Banks are increasingly moving beyond a two-bucket run/change view and adopting a three-tier model to improve transparency and reduce misclassification. A practical baseline for 2026 is a Run–Grow–Transform split that makes the operating cost impact of change visible.
| Category | Typical 2026 allocation (reference range) | What belongs here | Baseline question |
|---|---|---|---|
| Run (maintenance) | ~67–70% | Operations, mandatory controls, resilience commitments, vendor run contracts, technical debt servicing | Are we lowering unit cost without weakening control effectiveness? |
| Grow | ~22% | Enhancements and scaling of existing capabilities, automation with near-term value, capacity improvements | Is value measurable and does it avoid creating new run burden? |
| Transform (innovation) | ~11% | Modernization, new product platforms, data/AI foundations, operating model change, controlled decommissioning | Can we sustain delivery and control changes at scale? |
The executive failure mode is not “too much run.” It is unmanaged run: spend that grows because the estate is complex, controls are manual, and platforms cannot be simplified. The baseline should therefore be paired with decommissioning metrics and a view of duplicated capability.
Where 2026 spend is shifting: what is expanding, and why
AI: moving from pilots to production-scale operating capacity
Spending on AI is increasingly shifting from proof-of-concept activity to enterprise operating costs: model lifecycle controls, monitoring, data pipelines, security and privacy safeguards, and platform capacity. The spend baseline should therefore distinguish “AI as feature delivery” from “AI as platform capability,” because the latter creates ongoing run obligations (compute, controls, third-party dependencies, and talent).
Data infrastructure: the hidden driver of transformation affordability
Many banks are funding modernization of legacy data silos into real-time analytics and governed data products that can support AI and reporting at scale. In baseline terms, the key is whether data investment reduces cost and risk over time (through reuse and fewer reconciliations) or whether it becomes additive (new platforms while old ones remain). The baseline should therefore include an explicit view of platform retirement and duplication reduction.
Cybersecurity: a sustained growth curve tied to resilience expectations
Security and risk management spend continues to expand as banks respond to escalating threat activity, operational resilience expectations, and third-party concentration risk. A useful baseline links cyber spend to measurable outcomes (identity hardening coverage, patching and vulnerability performance, incident response readiness, and vendor controls) rather than treating it as an undifferentiated cost line.
Cloud: large spend, but the real question is unit economics
As cloud adoption broadens, the driver of spend is shifting toward AI workloads, data platform scale, and hybrid operating requirements. The baseline question is not “are we moving to cloud,” but whether cloud spend is improving unit economics and delivery velocity while maintaining resilience and control evidence. Banks that do not baseline cloud consumption and governance often experience cost surprises that erode transformation headroom.
Baseline disciplines that prevent “strategic vulnerability”
Make the run impact of change explicit before funding decisions
Every Grow and Transform initiative should declare its expected run impact: dual-running duration, incremental operations workload, control testing needs, monitoring coverage, and decommissioning commitments. This reduces the common pattern where projects are approved on benefits while their operating cost consequences appear later as unplanned run growth.
Track decommissioning and simplification as a portfolio KPI
The primary mechanism for freeing headroom is not budget negotiation; it is removing cost drivers. Baselines should include measurable retirement targets (applications, integrations, data stores, vendor contracts) and tie those targets to funding gates. Without this, the portfolio becomes additive and run intensity rises.
Use a consistent classification rulebook across technology, risk, and finance
Baselines break down when classifications are re-labeled to protect discretionary spend or to defer accountability. A defensible baseline uses stable rules that can be audited: what is mandatory, what is discretionary, how exceptions are handled, and who approves reclassification.
Establishing an objective baseline to validate investment ambitions
Strategy validation depends on more than headline growth rates. Leaders need evidence that the bank can fund and deliver change without degrading resilience, accumulating audit debt, or increasing run cost faster than volumes and revenue. An assessment-driven baseline supports this by testing whether portfolio artifacts are consistent, comparable, and tied to operational reality: category definitions, run obligations, decommissioning feasibility, and the control capacity to industrialize AI and modern platforms.
Within that approach, the DUNNIXER Digital Maturity Assessment can be used to evaluate whether current spend baselines provide enough decision confidence to prioritize and sequence investments. When assessment dimensions such as governance effectiveness, delivery discipline, resilience readiness, and evidence quality are evaluated against portfolio data and budgeting artifacts, executives can test whether ambitions are realistic given current digital capabilities, and where the portfolio must change before the strategy can scale safely.
Reviewed by
The Founder & CEO of DUNNIXER and a former IBM Executive Architect with 26+ years in IT strategy and solution architecture. He has led architecture teams across the Middle East & Africa and globally, and also served as a Strategy Director (contract) at EY-Parthenon. Ahmed is an inventor with multiple US patents and an IBM-published author, and he works with CIOs, CDOs, CTOs, and Heads of Digital to replace conflicting transformation narratives with an evidence-based digital maturity baseline, peer benchmark, and prioritized 12–18 month roadmap—delivered consulting-led and platform-powered for repeatability and speed to decision, including an executive/board-ready readout. He writes about digital maturity, benchmarking, application portfolio rationalization, and how leaders prioritize digital and AI investments.
References
- https://www.gartner.com/en/newsroom/press-releases/2026-02-03-gartner-forecasts-worldwide-it-spending-to-grow-10-point-8-percent-in-2026-totaling-6-point-15-trillion-dollars
- https://www.celent.com/en/insights/assessing-the-impact-of-tariffs-on-retail-bank-it-spending
- https://www.linkedin.com/pulse/bank-spending-use-metrics-improve-performance-chris-nichols-hpi2c
- https://thefinanser.com/2026/02/accentures-six-big-trends-in-banking-2026
- https://www.auvik.com/franklyit/blog/financial-services-it-trends/
- https://www.backbase.com/banking-predictions-report-2026/ai-and-the-future-of-banking
- https://www.accenture.com/us-en/insights/banking/accenture-banking-trends-2026
- https://sdk.finance/blog/core-banking-transformation-lead-with-strategy-execute-with-confidence/
- https://www.splunk.com/en_us/blog/learn/it-tech-spending.html
- https://www.privatebankerinternational.com/features/trust-and-technology-in-balance/
- https://www.wwt.com/wwt-research/ai-and-automation-in-banking-transforming-workplace-services
- https://www.gartner.com/en/newsroom/press-releases/2025-07-29-gartner-forecasts-worldwide-end-user-spending-on-information-security-to-total-213-billion-us-dollars-in-2025