Use Case
Multi-Source Reconciliation
Consolidate cash, holdings, and transactions into a single golden source using intelligent matching and automated root cause analysis.
Description
Reconciling cash, holdings, and transactions across multiple systems is complex due to data fragmentation, timing mismatches, and manual exception handling.
Our platform automates reconciliation by consolidating and harmonizing data into a single golden source. It uses AI-driven classification, enrichment, and customizable rules to handle complex portfolios at scale.
Key Features
- Automated ingestion and harmonization of multi-source data with intelligent reconciliation of holdings, transactions, and cash.
- AI-driven entity classification, enrichment, and proprietary resolution models to reduce unmatched breaks and handle incomplete data.
- Configurable rules engine with continuous learning from user feedback to improve matching accuracy over time.
- Centralized audit trail, collaboration tools, and full support.
Data Objects
- Funds/Sub-Funds
- Investment Products
- Cash Accounts
- Portfolio Positions (A, B, C, ...)
- Cash Positions (A, B, C, ...)
- Transactions (A, B, C, ...)
Intelligence
- Extract unstructured Data
- Classification model
- Entity Enrichment model
- Entity Recognition model
- Root cause analysis
“Asset managers must adapt quickly to meet investors' expectations and having a reliable partner like Next Gate Tech is essential for this transition.”
BJ
Benoît Joseph
Chief Risk Officer, Trustmoore
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