Financial services
Exception handling that a regulator can follow, at the speed the business needs.
Onboarding, payments exceptions and fraud operations run on deterministic rules first, self-hosted AI for interpretation second, and a named reviewer for the decision that matters.
- AI applied only where judgment is needed
- Rules firstAI applied only where judgment is needed
- on every consequential decision
- Named revieweron every consequential decision
- per case, end to end
- One recordper case, end to end
- models, no external data exposure
- Self-hostedmodels, no external data exposure
Operational pressures
The exception queue is where the real cost lives.
Straight-through processing handles the easy cases. Everything else lands on a person, and that queue is what determines turnaround time and audit exposure.
Exceptions grow faster than straight-through processing improves
Every new product, market or regulation adds another exception path that lands on an operations team's desk rather than in the core system.
Onboarding has to be fast and fully evidenced
Commercial onboarding competes on turnaround time, but every check performed and every waiver granted has to be reconstructable for a later review.
Fraud and financial crime signals arrive across disconnected systems
Payments, case management and customer data rarely share an owner, and a delay in correlating them is a delay in stopping loss.
Model risk governance applies to AI the same way it applies to any model
Institutions already run model risk frameworks; AI used in a workflow needs to sit inside that governance rather than beside it.
Systems typically in scope
What integrations usually need to reach.
- Core banking and policy administration
- Core banking, lending and policy administration systems reached through database, SAP RFC or vendor-specific interfaces.
- CRM and case management
- Customer relationship and case management platforms used by onboarding, operations and financial crime teams.
- Payments and clearing
- Payment gateways and clearing interfaces where exceptions and holds need enrichment before a decision.
- Document and KYC systems
- Document capture, identity verification and know-your-customer platforms feeding onboarding decisions.
- Data warehouse and reporting
- Data warehouses and reporting systems that consume decision outcomes for regulatory and management reporting.
Worked scenario: commercial onboarding
From application to provisioned account, with a full compliance trail.
Screening and risk-tiering are deterministic. The model reads free text. The analyst decides.
- 01
Trigger
A commercial customer submits an onboarding application through the portal.
- 02
Integration
Connector and database steps retrieve identity verification results, beneficial ownership data and sanctions screening output.
- 03
Rules + Code
Deterministic checks apply risk-tiering rules, document completeness checks and sanctions match thresholds.
- 04
Sovereign AI
A self-hosted model reviews submitted business descriptions and flags inconsistencies against the stated industry code.
- 05
Human Approval
A compliance analyst reviews the assembled case, the rule outcomes and the model flag, then approves, requests more information or declines with a reason.
- 06
System Action
The approved account is provisioned in the core banking system and the CRM record is updated.
- 07
Audit
Screening results, rule outcomes, model output, the analyst decision and the provisioning action are retained as one execution record.
Worked scenario: payments exception
A velocity flag, resolved without losing the audit trail.
A hold applies automatically under policy; a person confirms or releases it.
- 01
Trigger
A payment pattern trips a threshold rule for unusual velocity on an account.
- 02
Integration
Recent transaction history, device and channel signals, and prior case history are assembled from separate systems.
- 03
Rules + Code
Deterministic logic scores the pattern against known typologies and applies a temporary hold where policy requires one.
- 04
Human Approval
A fraud analyst reviews the assembled case and confirms the hold, releases it or escalates to investigation.
- 05
System Action
The confirmed decision is written back to the payments platform, releasing or maintaining the hold.
- 06
Audit
The full sequence, including the hold decision and its reason, is retained for regulatory reporting and later dispute handling.
Deployment and data control
Customer and transaction data does not need to leave the institution's environment to be automated.
Where regulation or internal policy restricts where financial data may be processed, deployment on infrastructure the institution controls answers that directly.
On-premises or private cloud deployment
The platform deploys inside the institution's data centre or private cloud, so transaction and customer data are processed inside infrastructure already subject to existing controls.
Self-hosted models under model risk governance
Because models run inside the deployment, they can be reviewed, versioned and governed under the institution's existing model risk framework rather than treated as an opaque external service.
Segregation of duties enforced at run time
Approval and publishing rights are separated by role, so the person who configures a rule is not automatically the person who can approve a case against it.
Evidence and reporting
What internal audit and regulators ask to see.
A case reconstruction should come from the execution record, not from asking three teams to remember what happened.
Per-case execution record
Screening data, rule outcomes, model output, reviewer decision and system write-back retained together.
Model output as a proposal
Model output is stored as what was proposed, distinct from what the reviewer actually decided.
Change history for rules and thresholds
Policy changes are versioned, so a past decision can be checked against the rules that were live when it was made.
Use cases
Processes financial services teams run on Nexus.
Each combines two or more systems in one governed run, with approval and audit.
HubSpot + Salesforce + SAP
Lead to account and ERP handoff
Marketing leads become clean sales accounts, and approved deals reach ERP without re-keying.
View use caseStripe + Xero + ServiceNow
Payment reconciliation and exception handling
Payments reconcile into accounting automatically, and mismatches become tracked exceptions.
View use caseCoupa + SAP + Microsoft 365
Invoice approval and procurement
Invoices are checked against procurement records and approved before they are created.
View use caseWorkday + Okta + ServiceNow + Microsoft 365
Identity changes for regulated staff
Access changes for regulated roles carry a case record, approval and full evidence.
View use caseStripe + NetSuite + Xero
Subscription revenue reconciliation
Billing events are compared with NetSuite and Xero, and differences are approved before correction.
View use casePayPal + Xero + ServiceNow
PayPal payment exception to service case
PayPal payment and subscription mismatches become approved, recorded corrections.
View use caseSAP Concur + SAP + Microsoft 365
Expense and budget governance
Budget changes are checked against policy, approved and followed up in SAP with notification.
View use caseRelevant capabilities
Where financial services deployments usually start.
Workflow Automation
Long-running case handling with branching and exception routing.
ExploreSovereign AI
Self-hosted models for document and narrative review.
ExploreHuman-in-the-Loop
Approval, correction and escalation as workflow steps.
ExploreGovernance and Audit
Segregation of duties and the case-level execution record.
ExploreProcurement notes
Working within vendor risk and model risk assessment.
Alignment language, not certification claims
Nexus capabilities can be described as aligned with or mapping to the control objectives referenced in a vendor risk assessment. Nexus does not claim a certification on the institution's behalf; the institution's compliance function remains responsible for its own accreditation and regulatory filings.
Architecture session
Bring us your exception queue, not just your straight-through rate.
We will walk through where deterministic rules already cover the case, where a self-hosted model can help an analyst read faster, and where the review has to stay exactly where it is.