IVP Reconciliation Solution

Hybrid Intelligence. Trusted Control.

How is a hybrid reconciliation model different from rules-only or AI-only systems?

A hybrid reconciliation model combines a rules engine with an AI layer and human supervision, where conventional solutions typically offer only one. In the IVP Reconciliation Solution, the rules engine stays the system of record, AI agents investigate and clear breaks, and a person verifies every close, so every break is traceable and every action is auditable.

How does human oversight work in the IVP Reconciliation Solution?

Human oversight in the IVP Reconciliation Solution is governed by confidence thresholds that determine which tasks are automated. Every automated action is recorded in the audit trail, and every close is verified by a person, keeping accountability with a named human.

What AI agents are included in the IVP Reconciliation Solution

The IVP Reconciliation Solution includes AI agents that work across the reconciliation lifecycle: an Enrichment Agent, a Middle Office Agent, a Matching Agent, an Annotation Agent, and a Sign-off Agent.

The Enrichment Agent surfaces CUSIP, ISIN, SEDOL, and LoanX identifiers before matching; the Middle Office Agent converts unstructured agent notices into validated data; the Matching Agent triages breaks and escalates unresolved items with context; the Annotation Agent applies historical remarks to recurring breaks; and the Sign-off Agent runs post-reconciliation health checks and produces a Go/No-Go summary for human sign-off.

Is every AI agent action auditable in the IVP Reconciliation Solution?

Every AI agent action in the IVP Reconciliation Solution is captured in the audit trail. Users get a complete audit history of user actions and automated validations, so explainability is built in rather than bolted on, supporting cleaner audits.

Can the IVP Reconciliation Solution handle intraday and month-end volumes?

The IVP Reconciliation Solution processes millions of records in minutes across intraday, daily, and month-end workloads. High-frequency runs catch breaks early to reduce settlement risk, and month-end close can run in parallel with daily activity to produce as-of-daily and as-of-month-end views.

Is the reconciliation process real-time or batch-based?

Reconciliation has recently transformed from a batch process to a real-time requirement, driven by increases in the pace of trading, the complexity of instruments, and the expectations from portfolio teams.
What sets the IVP Reconciliation Solution apart is how it handles timing mismatches, live data changes, and book adjustments mid-cycle. It acts on Geneva breaks, delayed pricing, and OTE mismatches in real time. Flexible logic and event-based triggers allow it to adapt to new file formats and sources without constant reconfiguration to deliver faster resolution times, cleaner books, and fewer surprises before reporting deadlines hit.

How does AI extract data from unstructured agent notices?

The AI capabilities within the IVP Reconciliation Solution identify individual data points within unstructured agent notices. Once identified, the solution extracts, validates, and structures the data into a standardized format. It effectively converts unstructured PDFs into structured data while performing data quality checks to improve accuracy in agent notice processing.