Governed AI footprint
148
Tools, copilots, workflows, vendors, and model usage under named ownership
Primary Market
Control enterprise AI in banking before unmanaged usage becomes supervisory, conduct, and data risk.
SENTRUM gives banks an Enterprise AI Firewall and audit-defensible AI governance layer across employee copilots, customer servicing, credit support, fraud operations, model usage, and third-party AI. It helps CIO, CISO, CRO, Compliance, and Internal Audit enforce policy in real time, reduce Shadow AI exposure, and prove control effectiveness under board and regulator scrutiny.
Enterprise AI FirewallShadow AI controlPrompt Guard enforcementAudit evidence ledger
Runtime control coverage
91%
Mapped to policy, owner, risk tier, obligations, and evidence
Escalated high-risk events
17
Sensitive interactions blocked, warned, or sent for supervisory review
Inspection readiness
24
Evidence packs and control records ready for audit and regulator review
Sector focusTier-1 Banking
Operating modelFirewall + governance
Review postureBoard, audit, regulator
DeploymentOn-prem / private / hybrid
Operating fit
Built for high-control banking environments
- Customer-data sensitive workflows
- Maker-checker operating model
- Policy enforcement in runtime AI usage
- Supervisory reporting and evidence readiness
Sector reality
Sensitive customer environments
Control posture
Embedded maker-checker
Deployment fit
Private, hybrid, on-prem
Scrutiny readiness
Supervisory inspection-ready
Why this industry is different
Control architecture for front office, operations, risk, and technology
Banking AI usage sits inside customer servicing, credit, fraud, operations, compliance, and vendor ecosystems. That means governance without runtime control is weak, and monitoring without evidence is not defensible. SENTRUM is designed for banks that need real-time enforcement, attributable decisions, and regulator-reviewable evidence.
Shadow AI sprawl
Unmanaged employee AI usage across front office, operations, risk, technology, and support creates immediate data leakage and conduct exposure.
Decision accountability
Credit, fraud, servicing, and investigative workflows require attributable oversight, escalation paths, and reviewable AI usage.
Policy enforcement
Runtime guardrails must be embedded so policy can be enforced consistently across employee, customer, and support interactions.
Third-party onboarding
External AI tools, copilots, and banking vendors need structured due diligence, onboarding controls, and ongoing monitoring.
Priority AI use cases
Structured workflows where governance must be operational, not aspirational.
SENTRUM supports banking workflows where AI adoption is growing but control expectations remain non-negotiable.
01 · Employee AI copilots
Employee AI copilots
Control employee-facing copilots for drafting, summarization, search, and operations support with real-time policy enforcement and attributable evidence.
Banking workflow
Employee AI copilots Illustrative sector workflow panel representing governed runtime control, evidence capture, and supervisory readiness.02 · Customer servicing AI
Customer servicing AI
Govern AI-assisted service workflows so customer interactions, data exposure, and escalation paths remain reviewable and controlled.
Banking workflow
Customer servicing AI Illustrative sector workflow panel representing governed runtime control, evidence capture, and supervisory readiness.03 · Credit and decision support
Credit and decision support
Keep AI-assisted underwriting and decision support inside named ownership, approved workflows, and evidence-backed supervisory control.
Banking workflow
Credit and decision support Illustrative sector workflow panel representing governed runtime control, evidence capture, and supervisory readiness.04 · Fraud and AML support workflows
Fraud and AML support workflows
Apply enterprise control to investigative support workflows where sensitive data, alerts, and analyst actions must remain defensible.
Banking workflow
Fraud and AML support workflows Illustrative sector workflow panel representing governed runtime control, evidence capture, and supervisory readiness.05 · Third-party AI onboarding
Third-party AI onboarding
Run due diligence, risk scoring, and approval workflow before external AI tools or banking vendors move into production use.
Banking workflow
Third-party AI onboarding Illustrative sector workflow panel representing governed runtime control, evidence capture, and supervisory readiness.Risk and control model
Map sector risk to required control and expected evidence.
Risk themes
Required controls
Evidence expectations
Unmanaged internal usage
Usage visibility, access policy, prompt control, and exception triage
User attribution, event history, and control action evidence
High-risk workflows
Named owners, review workflow, and monitoring thresholds
Decision lineage, reviewer actions, and remediation trail
Third-party risk
Due diligence workflow, contractual control expectations, and monitoring
Vendor dossiers, approvals, and periodic review outputs
How SENTRUM fits
Modules selected for this industry control model.
These modules are the highest-priority control capabilities for Banking organizations adopting AI under scrutiny.
AI Usage Visibility
Detect who is using what, where, and under which ownership structure.
Shadow AI Detection
Find unmanaged tools and convert findings into governed action.
Enterprise AI Firewall & Policy Enforcement
Apply runtime AI policy, prompt controls, and governed review gates consistently.
Audit Evidence Ledger
Reconstruct firewall, Prompt Guard, and control decisions under audit challenge.
AI Due-Diligence Workflow
Govern onboarding of third-party AI tools, models, and workflows.
Compliance Reports
Generate regulator-ready reports grounded in evidence, not narrative only.
Operating stakeholders
Multi-buyer relevance for enterprise sales, governance, and implementation.
CRO / Risk
See AI risk tiering, exception queues, control gaps, and remediation posture across banking workflows.
Compliance
See policy adherence, obligations mapping, control exceptions, and defensible reporting across regulated banking operations.
Internal Audit
Access exportable evidence lineage, reviewable decisions, and proof that control execution occurred as designed.
CIO / Technology
Assess deployment governance, integration fit, and how the operating model aligns with banking control expectations.
Deployment and architecture fit
Control architecture for front office, operations, risk, and technology
SENTRUM fits banking environments that need integration with policy, oversight, review workflow, and evidence generation without weakening segregation of duties or deployment controls.
Architecture notes
- Segregation of duties and maker-checker flow
- Policy and Prompt Guard integration points
- Evidence-first escalation and remediation workflow
Evidence and reporting
Designed for audit, executive review, and regulator-facing evidence requests.
Capture policy decisions, firewall outcomes, approvals, exceptions, and evidence packs so banking teams can respond credibly to audit, board, and supervisory requests.
FAQ
Decision-stage questions for deployment, control, and evidence.
Does the platform fit private cloud or on-prem deployment?
Yes. SENTRUM is designed for on-premises, private cloud, public cloud, and hybrid banking deployment models.
Can this support regulator or internal audit evidence requests?
Yes. SENTRUM produces attributable records, lineage, approvals, and evidence packs that support internal audit, risk, and supervisory review.
Does the platform fit private cloud or on-prem deployment?
Yes. SENTRUM supports on-premises, private cloud, and hybrid deployment models that fit controlled banking environments.
Next step
Move from banking AI interest to architecture-level control discussion.
Discuss how SENTRUM can establish Enterprise AI Firewall control, governed onboarding, evidence lineage, and regulator-defensible reporting across banking workflows.