Use Case
Proprietary Asset Enrichment Engine
Ensure regulatory-grade data completeness for private assets through intelligent enrichment and inference of missing attributes.
Description
Private market assets often lack complete data attributes required for regulatory reporting, risk analysis, and portfolio management. Manual data gathering is time-consuming and frequently incomplete.
Next Gate Tech's Enrichment Engine uses contextual AI trained on historical fund data to automatically identify comparable entities and intelligently populate missing attributes for private debt, secondaries, and bespoke structures, ensuring immediate reporting readiness.
Key Features
- Intelligent Data Inference: Automatically populate missing attributes using comparable entity analysis
- Multi-Source Data Aggregation: Pull enrichment data from internal history, market databases, and proprietary sources
- Confidence Scoring: Provide transparency on inferred data quality with validation metrics
- Regulatory Mapping: Ensure all required fields for reporting frameworks are populated
- Continuous Enhancement: Improve data quality as new information becomes available
Data Objects
- Asset Attribute Master
- Comparable Entity Database
- Enrichment Rules Library
- Data Quality Scorecards
- Regulatory Field Mappings
Intelligence Features
- Contextual similarity matching for comparable asset identification
- Predictive attribute inference based on asset characteristics
- Automatic classification of non-standard instruments
- Smart validation of inferred vs. actual data points
- Pattern recognition for systematic data gaps
- Learning algorithms that improve accuracy over time
- Risk-based prioritization of enrichment activities
“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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