Open Banking Consent Requirements as a Feasibility Test

Why consent is the control plane for open banking

In open banking and broader data sharing models, consent is not a user-interface feature. It is the control plane that defines the bank’s legal basis for disclosure, the scope of third-party access, and the conditions under which that access remains valid. When consent is underspecified, banks inherit ambiguity that expands operational risk: uncertain authorization boundaries, inconsistent customer communications, and fragile evidence under examination.

For executives validating an open banking strategy, the central feasibility question is whether the institution can run consent as an enterprise capability: consistent, auditable, and enforceable across channels, products, partners, and jurisdictions. This capability is often the limiting factor that determines whether data sharing ambitions can move beyond pilots without accumulating unbounded privacy, fraud, and compliance exposure.

What regulators and industry standards converge on

Explicit permission must be unambiguous

Consent must be obtained through an active, affirmative action by the customer, rather than through implied consent or default selections. This requirement is not only a privacy principle; it is a risk control that constrains later disputes about authorization and reduces the probability that access persists without a defensible customer decision.

Granularity defines the boundary of permissible access

Open banking consent is expected to be granular: customers should be able to choose which accounts and which data types are shared rather than approving blanket access. Granularity becomes operationally important because it forces banks and third parties to engineer access controls that are specific, testable, and enforceable, instead of relying on broad entitlements that are difficult to monitor and revoke precisely.

Purpose limitation is a governance requirement, not a disclosure

Purpose limitation requires that the customer understands why data is being accessed and that the data is used only for that stated purpose. The executive implication is that banks need policy and technical mechanisms to keep “purpose” from becoming a narrative label. Purpose has to be bound to entitlements, data minimization, retention rules, and monitoring so that misuse can be detected and acted upon.

Time-bounded access changes operating expectations

Time limits on consent shift banks from one-time onboarding controls to lifecycle governance. Expiration and reauthorization requirements introduce volume, cadence, and customer-experience considerations that can materially affect channel operations, call center demand, and partner service levels. Feasibility depends on whether renewal flows are reliable and whether termination is consistently enforced when consent expires.

Revocation must be practical and effective

Revocation is only meaningful if customers can view and withdraw permissions easily and the ecosystem can enforce revocation quickly. Executives should treat revocation as a negative control test: if the bank cannot reliably stop access when instructed, it cannot credibly claim control of downstream risk, regardless of how strong the initial authorization appears.

Transparency is inseparable from customer protection

Consent should clearly identify the third party, the data in scope, the purpose, and the duration, along with safeguards and customer rights. In practice, transparency reduces reputational risk by limiting “surprise outcomes,” such as unexpected data use or recurring access that customers did not anticipate. It also reduces operational friction by lowering disputes and complaint volumes tied to misunderstandings.

Security and authentication are built into the consent flow

Open banking consent is commonly paired with strong authentication for high-risk actions and token-based access patterns that avoid sharing customer credentials. The strategic point is that consent cannot be separated from the bank’s identity and access management capability: weak authentication or inconsistent token governance turns a well-designed consent policy into a theoretical control.

Auditability is the difference between policy and proof

Supervisory and internal assurance expectations require an audit trail showing when consent was granted, what was approved, how it changed over time, and how access was used. Auditability is often where feasibility breaks: banks may implement consent screens but fail to build end-to-end evidence, especially when multiple channels, third-party gateways, and partner systems are involved.

Consent as an operating model challenge

Cross-functional ownership is mandatory

Consent management spans product design, legal and privacy, security architecture, data governance, and third-party risk. If ownership remains fragmented, the institution typically experiences inconsistent interpretations of scope, uneven control enforcement, and gaps between contractual requirements and technical implementation. A viable model clarifies decision rights for consent language, entitlement structure, and exception handling.

Partner onboarding and ongoing supervision depend on consent discipline

Third-party providers introduce variability in how consent is presented, how data is requested, and how revocation is handled. Banks that treat partner onboarding as a one-time event often discover late that monitoring and reauthorization mechanics are weak. A feasible approach defines minimum consent and security requirements, evidence expectations, and escalation paths before data sharing is activated.

Data governance determines whether “granular” consent is actionable

Granularity requires that data categories are consistently defined and mapped to systems of record. If data taxonomy and metadata are inconsistent, banks cannot reliably restrict access to the customer-approved scope. In that case, the bank’s control posture depends on manual compensating controls, which rarely scale under high-volume API usage.

Designing for supervisory scrutiny without constraining innovation

Open banking strategies succeed when they can demonstrate that access is both controlled and enablement-oriented: partners can integrate efficiently, customers can manage permissions without friction, and the institution can evidence compliance without excessive manual intervention. Standards bodies and industry frameworks provide a common vocabulary for consent flows and data sharing patterns, but the burden of proof remains on the bank’s operating discipline.

For leadership teams, the strategic trade-off is clear. Looser consent patterns can accelerate early integrations but introduce latent risk that expands with scale. Tighter consent governance can reduce risk but may increase complexity in customer experience and partner integration. The feasibility test is not theoretical alignment with principles; it is whether the bank can execute the chosen balance consistently across its channels and partner ecosystem.

Validating open banking ambitions through digital maturity assessment

Testing strategic feasibility in open banking requires more than confirming that consent requirements are understood. Executives need decision-grade clarity on whether the bank’s current capabilities can sustain explicit, granular, time-limited, revocable, and auditable consent at scale, while also meeting security expectations and third-party governance demands. That assessment must connect policy intent to operational reality: identity controls, data taxonomy, API entitlement enforcement, monitoring coverage, evidence production, and partner oversight.

In that context, a structured maturity view provides a practical way to benchmark gaps and reduce roadmap risk. Used as a validation tool, DUNNIXER Digital Maturity Assessment helps leadership teams examine whether governance, data controls, security integration, and operating routines are strong enough to support the consent lifecycle implied by open banking ambitions, improving confidence in prioritization and sequencing decisions without relying on assumptions that only fail after scale is reached.

Reviewed by

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.