Transforming multi-asset reconciliation with NeoXam Aro
Multi-asset reconciliation becomes increasingly difficult to scale when high transaction volumes, multiple custodians and manual processes come together.
For one financial service provider, reconciliation covered Bank Loans, Equities, Fixed Income, Derivatives and Structured Products across multiple custodians. Yet much of the process still depended on manual data extraction, macro runs, line-by-line matching and break commentary.
With NeoXam Aro, the client replaced this fragmented approach with an automated and centralized reconciliation framework, delivering 90%+ automation while significantly improving control and transparency across asset classes and custodians.
The challenge of multi-asset reconciliation
Reconciling one asset class is demanding. Managing high reconciliation volumes across several asset classes and custodians adds another level of operational complexity.
For this client, many of the most time-consuming activities were still handled manually.
Teams were:
- Extracting data
- Running reconciliation macros
- Matching transactions line by line
- Identifying reconciliation breaks
- Writing commentary to explain breaks
- Working with processes that varied between custodians
This reliance on manual processing made reconciliation slow and costly while maintaining a persistent risk of human error. As volumes increased, the existing operating model struggled to keep pace.
The client needed a more scalable way to manage reconciliation across asset classes and custodians.
Moving from Manual to Automated Reconciliation
NeoXam Aro provided the foundation for a new reconciliation framework.
Instead of relying on fragmented manual workflows, the client moved towards an automated and centralized model built around consistent processing and greater control.
The framework brought together four core capabilities.
Automated data ingestion and normalization
Data is ingested and normalized so that it arrives clean and standardized, removing the need for the manual handling previously required.
Rule-based auto-reconciliation
A rule-based auto-reconciliation engine applies consistent matching logic in the same way every time.
Intelligent classification
Items are classified into four categories:
- Auto Match
- Manual Match
- Match within tolerance
- Break identification
Centralized control
Reconciliation across custodians and asset classes is brought together in one place, creating a more consistent view of the process.
Together, these capabilities moved the client away from a manual, error-prone process towards a more automated and scalable model.
The result: 90%+ automation
The shift delivered a significant change in how the client managed reconciliation.
The new framework achieved 90%+ automation while providing greater control and transparency across multiple asset classes and custodians.
Fewer manual touchpoints also meant fewer opportunities for error. At the same time, consistent reconciliation logic was applied across books, while full match history and clear tolerance rules strengthened auditability.
However, the 90%+ automation rate is only part of the transformation.
Scale multi-asset reconciliation without scaling manual work
As reconciliation volumes increase, relying on more manual processing makes the operating model harder to sustain.
This use case shows how NeoXam Aro enabled a financial service provider to bring more automation, consistency and centralized control to reconciliation across multiple asset classes and custodians.
Download the use case below to see the complete challenge, approach and results.
