At a Glance
A bank technology exam baseline is a measurable control-and-evidence model that converts supervisory guidance into specific control requirements, traceable artifacts, and repeatable workflows that examiners can test during regulatory examinations.
For 2026, the baseline specifies what a bank must be able to demonstrate—across identity governance, cyber resilience, cloud configuration control, incident readiness, and third-party oversight—so exam teams can validate implemented control effectiveness and evidence quality, not just documented policy intent.
What Is a Bank Technology Exam Baseline?
Operationally, the baseline is the bank's working control map for exam preparation: it connects each supervisory expectation to accountable owners, in-scope systems, measurable thresholds, testing cadence, and evidence retrieval workflows so teams can prove ongoing control performance under challenge.
2026 Technology Supervision Shifts for Banks
Shift 1: FFIEC CAT sunset requires explicit framework ownership
- What changed: CAT completion is no longer an acceptable shorthand for cyber readiness.
- Why it matters: banks must justify their selected control framework and implementation method.
- Exam implication: examiners challenge rationale, not just checklist completion.
- Evidence expected: framework mapping, control test cadence, and remediation records.
Shift 2: Cybersecurity is examined across the full system lifecycle
- What changed: handbook updates emphasize build-run-retire continuity.
- Why it matters: control seams between engineering and operations are now exam-visible.
- Exam implication: policy-only answers are weaker than operating evidence trails.
- Evidence expected: secure change records, vulnerability closure metrics, and lifecycle governance logs.
Shift 3: Risk-based supervision increases materiality scrutiny
- What changed: scope is increasingly tailored to risk concentration and service criticality.
- Why it matters: control intensity must match material risk exposure.
- Exam implication: banks must explain why controls differ by system, vendor, or process.
- Evidence expected: critical service maps, dependency models, and risk-tiered control ownership.
2026 Bank Technology Exam Baseline Checklist
| Domain | Baseline expectation | Evidence artifact |
|---|---|---|
| Identity governance | Reliable lifecycle control and privileged containment | Access reviews, deprovisioning SLAs, PAM session records |
| Cloud configuration control | Risk-tiered baselines for critical workloads | Configuration standards, exception logs, drift remediation records |
| Vendor dependency monitoring | Service criticality-based third-party oversight | Tiering model, due diligence packets, ongoing monitoring logs |
| Incident response integration | Notification thresholds with decision rights and timing discipline | Playbooks, tabletop evidence, post-incident findings closure |
| Technology risk governance | Board and management traceability for material decisions | Committee records, issue registers, risk acceptance decisions |
| AI and model oversight | Governed high-impact use cases with explainability controls | Use-case inventory, validation evidence, change approvals |
2026 Bank Technology Exam Baseline — Structured Control & Evidence Table
The following table translates supervisory expectations into measurable controls, traceable evidence artifacts, and the types of questions examiners typically ask during technology reviews.
| Domain | Baseline Expectation | Evidence Artifact | Examiner Question |
|---|---|---|---|
| Identity Governance & Access Control | Access rights are risk-tiered, role-based, periodically reviewed, and aligned to least-privilege principles across all critical systems. | Access certification reports; role mapping documentation; privileged access review logs; joiner/mover/leaver workflow records. | How do you demonstrate that privileged and high-risk access is reviewed and revoked in a timely manner? |
| Cloud Configuration & Change Control | Cloud workloads are governed by defined configuration baselines, automated monitoring, and risk-tiered change approval workflows. | Configuration baseline documents; cloud posture management reports; change tickets; exception approvals with remediation timelines. | How do you validate that production cloud configurations remain within approved risk tolerances? |
| Vendor & Third-Party Monitoring | Critical vendors are classified by risk tier, continuously monitored, and subject to documented performance and security oversight. | Vendor inventory with risk tiers; SLA performance dashboards; SOC report reviews; remediation tracking logs. | How do you demonstrate ongoing monitoring of critical technology vendors beyond contract signing? |
| Incident Response & Technology Resilience | Incident response processes are operationalized with defined escalation paths, testing cadence, and integrated recovery controls. | Incident runbooks; tabletop test results; recovery time objective (RTO) validation reports; post-incident reviews with action tracking. | Can you provide evidence that response and recovery controls are tested and improved regularly? |
| Technology Risk Governance | Technology risks are formally identified, risk-rated, tracked, and reported to senior management with defined ownership. | Risk register extracts; board or committee reporting packs; risk acceptance documentation; mitigation status logs. | How does senior management gain visibility into technology risk posture and remediation progress? |
| Data Governance & Integrity | Data elements supporting regulatory or financial reporting are defined, lineage-documented, and subject to measurable quality controls. | Data lineage diagrams; data quality rule results; defect tracking logs; data ownership assignments. | How do you evidence that regulatory reporting data is complete, accurate, and traceable to source systems? |
| AI & Model Oversight | AI and advanced analytics models are inventoried, risk-tiered, monitored, and subject to governance controls aligned with model risk expectations. | Model inventory; validation documentation; monitoring dashboards; change/version logs; governance approvals. | How do you govern AI or advanced analytics models and monitor their ongoing performance and risk exposure? |
| Control Lifecycle Management | Controls are not static; they are documented, monitored, tested, and updated as systems evolve. | Control testing logs; control design documentation; exception tracking; internal audit findings and remediation records. | How do you ensure that implemented controls remain effective as systems and risks change? |
This baseline table is not a policy checklist. It represents a control-and-evidence model. In 2026 supervisory environments, examiners increasingly evaluate whether controls are operational, measurable, and supported by traceable artifacts - not merely documented in policy statements.
What Examiners Look for as Baseline Proficiency
Across federal supervision contexts, examiners tend to converge on one standard: controls must be operational, measurable, and maintainable. Baseline proficiency is demonstrated when the bank can trace a risk to owner, control, test result, and remediation status without narrative gaps.
- Identity and access reliability: lifecycle quality, MFA strength, and privileged governance.
- Cyber control resilience: patching discipline, monitoring coverage, and exercised response plans.
- Third-party control realism: concentration risk awareness and enforceable oversight obligations.
- Operational resilience continuity: critical-service dependency mapping and tested recovery capability.
- Evidence readiness: artifacts that are time-bound, attributable, and challenge-ready.
From Guidance to Baseline: Translating Supervision into Measurable Controls
Generic compliance summaries rarely help under examiner challenge. Banks need a measurable baseline that translates guidance into repeatable operating evidence, including control ownership, exception governance, and remediation deadlines that can be audited quickly.
Why Policy-Only Readiness Fails in 2026 Exams
- Written policies do not prove implemented controls: exam teams test operating execution, not policy intent alone.
- Evidence traceability is now a primary test point: controls must connect to artifacts that are retrievable, attributable, and time-bound.
- Control lifecycle documentation matters: banks need records showing controls are monitored, tested, updated, and remediated as systems change.
- Risk-tiered enforcement is expected: higher-risk systems and workflows should show stronger control intensity, tighter thresholds, and faster escalation paths.
For adjacent control priorities, see IAM sequencing gates for banking, vendor dependency risk mitigation, and digital banking maturity benchmarking.
People Also Ask: 2026 Bank Technology Exams
What is a bank technology exam baseline?
A bank technology exam baseline is a measurable control-and-evidence model linking supervisory expectations to owned controls, thresholds, and testable artifacts. It gives exam teams a clear way to verify whether risk controls operate in practice across critical systems, rather than relying only on policy statements.
How should banks prepare for 2026 IT exams?
Banks should prepare by mapping supervisory expectations to in-scope systems, accountable owners, measurable thresholds, and evidence workflows. Prioritize identity, cloud configuration, incident readiness, third-party monitoring, and risk governance artifacts. Preparation should be challenge-oriented so evidence can be produced quickly and consistently during examination windows.
What evidence do examiners expect?
Examiners usually expect objective artifacts such as access certifications, privileged activity logs, cloud and change control evidence, vulnerability metrics, incident exercise results, and remediation tracking. Evidence should be time-bound, owner-attributed, and linked to specific supervisory expectations so control effectiveness can be validated under direct challenge.
How does AI oversight factor into technology exams?
AI oversight is increasingly examined as part of core technology risk management. Banks should maintain model inventories, risk tiers, validation records, monitoring dashboards, and change logs. Examiners focus on governance ownership, performance drift controls, and whether high-impact AI decisions remain explainable and operationally controllable.
Is FFIEC CAT still used?
FFIEC CAT is no longer used as a default assessment shortcut. Banks now need a clearly justified framework and evidence-led control approach aligned with current handbook and supervisory expectations. The emphasis is on demonstrable implementation, monitoring, and remediation discipline, not completion of a single legacy template.
Establishing an Objective Baseline to Prioritize Realistic Ambitions
An objective baseline clarifies what can be accelerated safely, what must be remediated first, and where hidden supervisory risk could derail execution. It converts technology ambition into sequenceable decisions grounded in evidence quality and control readiness.
Used in that way, the DUNNIXER Digital Maturity Assessment helps leadership teams validate strategic ambition against current control maturity, evidence quality, and operational resilience constraints.
Key references
- https://ithandbook.ffiec.gov/
- https://www.occ.treas.gov/news-issuances/bulletins/2025/bulletin-2025-24.html
- https://www.fdic.gov/news/financial-institution-letters/2024/updated-ffiec-it-examination-handbook-development
- https://www.cisa.gov/resources-tools/services/cyber-security-evaluation-tool-cset
- https://www.pwc.com/us/en/services/consulting/cybersecurity-risk-regulatory/library/ffiec-operational-resilience.html
Additional reading
Frequently Asked Questions
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.