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Business Solution

Payments

Controlled payment workflows across finance and operations.

Payment operations are not only transactions. They involve authorisation, account context, fraud checks, customer instructions, reconciliation, audit evidence and exception handling.

Finance and operations professionals reviewing data, controls and exceptions.
Payments starts with people trying to make the right call. Finance needs to reconcile bank, ledger and transaction records faster.

Solution / Payments

A practical operating model for this environment

Advanze solutions describe how products, workflows, data, integrations and agents work together to solve an operating problem. For Payments, the focus is practical transformation: reducing fragmentation, creating reliable execution paths and giving people better control over work that crosses teams and systems.

The value is strongest when the capability is connected to adjacent processes. Records, workflows, controls, communications and analytics should participate in a shared execution fabric rather than live in separate tools.

Finance and operations professionals reviewing data, controls and exceptions.
Where Payments becomes real work people can trust. Finance, data and control work made visible through review, exception handling and accountable decisions.

Core capabilities

What Payments enables

Each capability is designed to work as part of the broader execution platform rather than as a disconnected module.

Payment requests

Use payment requests as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Approval routing

Use approval routing as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Exception handling

Use exception handling as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Finance controls

Use finance controls as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Reconciliation context

Use reconciliation context as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

Audit evidence

Use audit evidence as part of one operating model, with shared data, governed workflows, auditable actions and AI agents that can execute work while people stay in control.

The Advanze Control Model - AI Agents Execute Work Inside the Control Model

Agentic operating model

AI agents execute work inside the control model

Advanze treats AI agents as participants in the operating model. Agents can read context, call services, update records, trigger workflows, prepare decisions and escalate exceptions. Human teams remain responsible for judgement, governance and business accountability.

The goal is to create an execution platform where work can move across functions with consistent permissions, policies, audit trails and data visibility.

Business outcomes

What becomes possible

Unified operating modelConnect the workflows, data and decisions that drive outcomes.
AI-enabled capacityScale work with governed agents rather than only headcount.
Modernised processReplace fragmented tools with composable services.
Clear transformation pathMove from pilot to measurable adoption through phased delivery.
Finance and operations professionals reviewing data, controls and exceptions.
The outcome is not just automation. It is confidence in what happens next. When Payments runs inside a governed execution model, teams can move faster without losing judgement, accountability or trust.

Agentic use case

Where Payments becomes governed execution.

Finance needs to reconcile bank, ledger and transaction records faster.

What makes it harder in the real world: Reconciliation touches financial controls, auditability, thresholds, reason codes, journal proposals, segregation of duties and evidence requirements. Speed without control can create material risk.

What Advanze changes: Use agents to gather statements, ledger extracts, rules and prior exceptions, then propose safe matches and route unresolved items for review without posting journals automatically.

Data Preparation AgentPulls statements, ledger extracts and transaction files for the same period.
Matching AgentApplies safe matching rules for exact matches, known offsets, reversals, duplicates and timing differences.
Finance Policy AgentChecks thresholds, reason codes, account mappings and approval requirements.
Exception AgentGroups unresolved items, proposes likely causes and drafts follow-up notes.
Human Finance ReviewerApproves exceptions, journal templates and material decisions.
Challenge

Reconciliation touches financial controls, auditability, thresholds, reason codes, journal proposals, segregation of duties and evidence requirements. Speed without control can create material risk.

Orchestration

Use agents to gather statements, ledger extracts, rules and prior exceptions, then propose safe matches and route unresolved items for review without posting journals automatically.

Success

Use agents to gather statements, ledger extracts, rules and prior exceptions, then propose safe matches and route unresolved items for review without posting journals automatically.

Finance and operations professionals reviewing data, controls and exceptions.
Finance control 10Finance, data and control work made visible through review, exception handling and accountable decisions.
Finance and operations professionals reviewing data, controls and exceptions.
Finance control 11Finance, data and control work made visible through review, exception handling and accountable decisions.
Finance and operations professionals reviewing data, controls and exceptions.
Finance control 12Finance, data and control work made visible through review, exception handling and accountable decisions.

Why AI execution needs architecture

The work needs context, controls and clear permissions before automation can safely act.

That is why the Advanze control model matters: identity, permissions, policies, workflow, audit evidence and human judgement are embedded into execution before agents act.

  • Reconciliation touches financial controls, auditability, thresholds, reason codes, journal proposals, segregation of duties and evidence requirements. Speed without control can create material risk.
  • The right agent must receive the right context, tools, permissions and approval path before work moves forward.
  • Audit evidence, exception handling and human judgement need to be part of the workflow, not notes added after the fact.

Implementation path

How to move from concept to production

Advanze can be introduced progressively. Start with a visible workflow, prove the operating model, then expand into adjacent capabilities as the platform foundation matures.

  1. 1
    Assess the current operating model

    Map workflows, systems, data sources and manual coordination points around this capability.

  2. 2
    Design the target execution flow

    Define data, approvals, agent tasks, service calls and governance controls.

  3. 3
    Launch a focused implementation wave

    Start with a bounded use case that proves the operating pattern and creates reusable platform assets.

  4. 4
    Scale across the business

    Extend the pattern to adjacent workflows, more agents, more users and deeper integrations.

Next step

Build this into your execution platform roadmap

Explore how Payments can be implemented as part of a broader Advanze platform adoption programme.