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Digital Banking 2026: Establishing a Current-State Baseline for AI-Native Scale

Baseline language that keeps transformation governance objective, comparable, and decision-useful

InformationFebruary 19, 2026

Reviewed by

Ahmed AbbasAhmed Abbas

At a Glance

Describes a current state assessment for digital banking that evaluates customer journeys, technology architecture, data quality, controls, performance, and costs to identify gaps, prioritize investments, and define measurable targets for resilient, value-driven transformation.

Why “current state” needs baseline language, not narrative

In 2026, digital banking is no longer defined by isolated pilots or channel digitization. For executive teams, the current state is the bank’s measurable starting point across customer adoption, technology enablement, and regulated risk outcomes. The operational risk is that “current state” becomes a storyline: different functions describe different baselines, progress is framed as output rather than outcome, and sequencing decisions are made without a stable reference point.

Baseline language solves this by forcing three disciplines into governance: (1) a shared vocabulary for what the bank is measuring, (2) an explicit unit of comparison across business lines and platforms, and (3) refresh rules that keep the baseline credible as AI and digital asset capabilities evolve. The goal is not to produce a glossy diagnostic; it is to create decision-quality evidence that can be used to prioritize investment, set tolerances, and defend choices under supervisory and board scrutiny.

Market dynamics and adoption signals that shape the 2026 baseline

Growth rates are a context marker, not a strategy

External market sizing is useful baseline context because it frames competitive intensity and capital allocation pressure. One widely cited estimate places the global digital banking market at US$35.3 billion in 2024, growing to US$79.4 billion by 2030 (14.5% CAGR). The governance implication is not that every bank must “chase the CAGR,” but that digital capabilities are now being priced into expectations for speed, cost-to-serve, and product iteration cadence. ([marketresearch.com](https://www.marketresearch.com/Global-Industry-Analysts-v1039/Digital-Banking-42588740/?utm_source=chatgpt.com))

The customer tipping point is real, but primary relationships lag

Adoption in leading markets increasingly resembles a tipping point: in the UK, roughly half of adults are reported to use at least one neobank, yet the vast majority still keep their primary accounts with incumbent banks for perceived safety, credit products, and mortgages. Baseline language should therefore separate “reach” (accounts held) from “depth” (primary relationship, product breadth, and revenue relevance). ([finextra.com](https://www.finextra.com/blogposting/30786/incumbents-trap?utm_source=chatgpt.com))

Geographic leaders reset expectations for digital-first trust

Strategic consolidation is an operating-model signal

2026 deal commentary points to rising fintech M&A and strategic acquisitions by incumbents and established fintechs. For transformation governance, this matters because acquisitions change baselines: they introduce parallel platforms, duplicated control environments, and inconsistent customer experience standards unless baseline definitions are applied immediately across the combined estate. ([lexology.com](https://www.lexology.com/library/detail.aspx?g=6cffcbe7-6066-4f69-b05e-a6332de5cf01&utm_source=chatgpt.com))

Core technological shifts that must be captured in baseline terms

From “digital channels” to embedded and invisible banking

Digital banking is increasingly becoming “invisible” in the sense that services are embedded directly into customer workflows: payments in commerce journeys, lending at point of need, and treasury actions inside enterprise platforms. A current-state baseline should name the distribution reality explicitly: which journeys are owned by the bank, which are brokered through partners, and where the bank is providing regulated capabilities inside third-party experiences.

Agentic AI changes what “automation” means

As agentic systems progress beyond conversational interfaces into task execution, the baseline must describe not only the presence of AI, but where autonomy is permitted and how it is constrained. In governance terms, “AI-native” is not a label; it is a set of boundaries: what decisions can be made without human initiation, what approvals are required, what evidence is retained, and what monitoring triggers intervention. This baseline framing becomes essential for functions such as liquidity optimization, operational reconciliation, or proactive risk actions where small model errors can compound quickly.

Composable core platforms require a baseline of interoperability

For many banks, composability is no longer aspirational. One cited industry claim is that more than 65% of banks are exploring next-generation core platforms. Whether or not a specific percentage applies to a given institution, baseline language needs to reflect the reality that “core” is now an integration problem: APIs, eventing, identity, entitlement, and data contracts define the operating constraints. The baseline should therefore include measurable interoperability indicators such as API coverage for priority products, latency and availability targets, and data contract conformance rates. ([sdk.finance](https://sdk.finance/mambu-vs-finacle-alternative/?utm_source=chatgpt.com))

Embedded finance and BaaS baselines should be framed as regulated exposure

Embedded finance expands distribution but also expands accountable exposure. Market forecasts vary widely by definition; one recent projection places Banking-as-a-Service growth from US$26.47 billion in 2026 to US$108.03 billion by 2034. Regardless of which forecast a bank uses, governance baselines should focus on controllables: partner onboarding standards, transaction monitoring coverage across partners, dispute handling SLAs, and the bank’s ability to evidence compliance when the customer relationship is intermediated. ([fortunebusinessinsights.com](https://www.fortunebusinessinsights.com/bank-as-a-service-market-107038?utm_source=chatgpt.com))

Regulatory and security landscape: baseline language that survives scrutiny

Digital assets: distinguish legal frameworks from implementation readiness

Where digital assets intersect with payments and consumer propositions, baseline language must separate “regulatory clarity exists” from “the bank can operate compliantly at scale.” In the United States, the GENIUS Act (Guiding and Establishing National Innovation for U.S. Stablecoins Act) was enacted on July 18, 2025, establishing a framework for payment stablecoins. Practical implementation continues to evolve through regulator procedures and rulemaking activity. A credible baseline therefore records what the bank can evidence today: custody and issuance roles (if any), reserve and attestation controls, transaction monitoring coverage, and legal entity responsibilities. ([congress.gov](https://www.congress.gov/bill/119th-congress/senate-bill/1582/text?utm_source=chatgpt.com))

AI governance: explainability and auditability as baseline requirements

In the EU, AI governance expectations increasingly require that high-risk uses—such as creditworthiness and credit scoring—are supported by documentation, transparency controls, and ongoing monitoring. The baseline should explicitly describe the bank’s evidence posture: model inventories, traceability of training and production data, human oversight points, and the ability to reproduce decisions for audit and challenge. This framing avoids a common failure mode where “AI governance” is described as a policy set rather than an operationally testable control system. ([eba.europa.eu](https://www.eba.europa.eu/sites/default/files/2025-11/d8b999ce-a1d9-4964-9606-971bbc2aaf89/AI%20Act%20implications%20for%20the%20EU%20banking%20sector.pdf?utm_source=chatgpt.com))

Deepfake defense: make the baseline measurable in outcomes

AI-enabled impersonation and deepfakes are changing fraud economics. One widely referenced projection from the Deloitte Center for Financial Services suggests AI-enabled fraud losses could reach US$40 billion in the United States by 2027, reinforcing the need for layered defenses. Baseline language should specify outcome metrics and control triggers: detection rates, false-positive burdens, time-to-intervention, step-up authentication rates, and the governance rules for high-value transfers (including multi-person approvals where warranted). ([deloitte.com](https://www.deloitte.com/us/en/insights/industry/financial-services/deepfake-banking-fraud-risk-on-the-rise.html?utm_source=chatgpt.com))

Customer experience benchmarks: baselining what customers will not tolerate

Personalization expectations require a baseline for data readiness

Customer expectations continue to consolidate around personalization. A frequently cited figure is that 72% of customers rate personalization as “highly important” in financial services. Governance baselines should translate this into operational terms: consent coverage, identity resolution rates, decision latency, and controls that prevent personalization from becoming discriminatory targeting. ([zendesk.com](https://www.zendesk.com/blog/customer-experience-in-banking/?utm_source=chatgpt.com))

Hybrid models: physical is being redefined, not removed

Even as digital-first becomes the default, customer preference data suggests that physical formats still matter for complex needs. Accenture reports that 76% of respondents would use micro-branches or smart booths. The baseline should therefore include channel orchestration measures (handoff quality, context continuity, appointment-to-resolution rates) rather than treating “branch vs digital” as a binary. ([accenture.com](https://www.accenture.com/us-en/insights/banking/accenture-banking-trends-2026?utm_source=chatgpt.com))

Service speed: define “immediate” as an SLA, not a slogan

Speed has become a baseline expectation. One commonly cited statistic is that 72% of customers want immediate service, and multiple sources point to a willingness to pay more for convenience in certain contexts. For governance purposes, the baseline should specify what “immediate” means in each journey (fraud disputes, card replacement, mortgage milestones, business onboarding), and the operational constraints that determine whether speed is achieved through automation, staffing, or simplification. ([zendesk.com](https://www.zendesk.com/blog/customer-experience-in-banking/?utm_source=chatgpt.com))

Baseline language executives can use to govern transformation

To keep baselining objective, executives benefit from consistent terms that travel across technology, risk, operations, and product. The following baseline language is designed to remove ambiguity without relying on subjective scoring labels:

  • Scope baseline: which entities, products, channels, and journeys are in-scope, and what is explicitly excluded.
  • Outcome baseline: customer, operational, and risk outcomes that must not degrade during change (e.g., fraud loss rate, sanctions screening timeliness, uptime and latency, complaint closure time).
  • Evidence baseline: the minimum artifacts required to support an assertion (logs, audit trails, model documentation, exception records, control test results).
  • Interoperability baseline: the measurable integration posture (API coverage, data contract compliance, identity/entitlement consistency, event observability).
  • Resilience baseline: the service tolerances and recovery assumptions for critical journeys and third-party dependencies.
  • Change baseline: refresh triggers that require baseline recalibration (platform migration, model replacement, policy changes, material vendor changes, acquisition integration milestones).

This vocabulary matters because it creates a common decision grammar. Without it, transformation programs can “advance” while the organization’s ability to evidence compliant outcomes becomes weaker—particularly as agentic AI and embedded distribution expand the surface area of regulated responsibility.

Strengthening baseline governance to sequence change with confidence

Objective baselining becomes harder as the bank’s delivery model becomes more distributed: agentic AI introduces new monitoring requirements, embedded finance multiplies third-party dependencies, and digital-asset capabilities introduce new legal and control expectations. A structured assessment of digital capabilities provides a way to test whether the bank’s baseline language is supported by real enabling discipline: data quality, model governance evidence, observability, ownership clarity, and independent challenge strength.

By mapping those enabling disciplines to the same outcome and evidence baselines executives use to govern transformation, the DUNNIXER Digital Maturity Assessment can be used to evaluate readiness and sequencing risk without relying on subjective narratives. The value in governance terms is decision confidence: leaders can identify where baseline statements are not yet defensible, where measurement is inconsistent across lines of business, and where the operating model will become a constraint as AI-native capabilities move from bounded pilots into scaled production.

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Reviewed by

Ahmed Abbas
Ahmed Abbas

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.

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