Use Case · Finance Operations

Reconcile millions of transactions with governed agentic execution.

Nexoraa replaces manual matching and exception triage with multi-agent workflows that ingest statements, match transactions, identify breaks, propose corrections, and route only the genuine exceptions to a human - with full audit trail.

Why It Breaks

Why reconciliation breaks at scale

Reconciliation is one of the most expensive recurring operations in any large enterprise. Statements arrive in inconsistent formats from dozens of counterparties. Matching rules change constantly. Exceptions stack up. Period close slips. Auditors raise findings. Most teams fall back on spreadsheets, ad-hoc scripts, and a small number of tenured staff who hold the institutional knowledge in their heads.

Pain Cards

The recurring failure points.

Inconsistent input formats

PDF statements, CSV exports, swift messages, and ERP extracts arrive in different formats from different counterparties, none stable over time.

Brittle rule-based matching

Static rule engines miss legitimate matches and surface false breaks; tuning rules introduces silent regressions elsewhere.

Exception backlog

Thousands of breaks per day mean analysts spend more time triaging than resolving; period close slips.

Lost institutional knowledge

Resolution logic lives in the heads of senior staff; when they leave, accuracy degrades.

Audit pressure

Auditors want evidence of every match decision and every exception treatment.

Execution Pipeline

How Nexoraa executes this workflow.

Nexoraa decomposes reconciliation into a multi-agent pipeline. Each agent has a single responsibility, a defined output schema, and a validation gate. Human approval is required only where policy specifies it.

01

Ingestion Agent

Accepts statements in supported formats and normalises every record into a validated JSON schema.

02

Matching Agent

Applies rule-based logic for structured fields and semantic matching for fuzzy fields, returning high-confidence matches with cited reasoning.

03

Break Identification Agent

Classifies unmatched records as timing, FX, fee, mis-booking, or true breaks and writes rationale into the audit trail.

04

Resolution Proposer Agent

Proposes a resolution drawn from prior cases, memory, and deterministic policy rules.

05

Haluvance Validation

Validates each output against schema, confidence threshold, and policy before promotion.

06

Human-in-the-Loop

Routes material or low-confidence items to a queue with context, evidence, and the agent's proposal.

07

Posting Agent

Posts approved entries to the ERP, captures the journal ID, and closes the break in the audit trail.

Integrations

Where this workflow plugs in.

SAP, Oracle ERP, Workday, Microsoft Dynamics, NetSuite, custom GL systems, banking partners, SWIFT, ISO 20022, host-to-host feeds, SharePoint, Box, and S3.

Outcomes

Outcomes our customers measure.

Exception volume

Fewer items reach a human queue because policy-resolvable cases are auto-resolved.

Time to close

Period close compresses because matching, classification, and posting run continuously.

Audit posture

Every match, classification, and treatment carries a citation and stored rationale.

Knowledge retention

Episodic memory captures resolution patterns so turnover stops degrading accuracy.

Governance

Posting actions sit behind policy gates and approval workflows.

Governance

How Nexoraa governs this workflow.

Nexoraa enforces role-based tool governance, deterministic policy gates, full lineage from statement line to journal entry, and Haluvance enforcement on every agent action. The complete execution trace is retained per the customer's compliance policy.

Why Nexoraa

Why Nexoraa for this workflow.

Multi-format ingestion

Production-grade extraction across PDF, structured, scanned, and message-based formats.

Deterministic + intelligent

Rule logic is deterministic where regulators demand it; agentic where judgement helps.

Recoverable execution

Checkpoint and resume mean downstream failures do not require starting from scratch.

Full traceability

Every match cites records, every break cites reasoning, every approval logs operator identity.

Next Step

See this workflow run on your data shape.

Bring a sample dataset under NDA. We will demonstrate the workflow on it.