Real-time service charge intelligence powered by machine learning and building-level aggregation across the UK property market
Combine service charge data with registered leases and ground rent for complete leasehold cost analysis.
Service Charge Data is a continuously-evolving intelligence layer that provides annual service charge data for leasehold properties across the UK. Built on our property graph, the dataset combines verified records with ML-powered estimates that improve automatically as our network expands.
When available, we surface exact recorded service charges from our property model. For properties without direct records, our machine learning models calculate estimates using real-time building-level aggregation, analysing comparable properties within the same building or spatial proximity. The system self-improves as new property data flows through the network, making estimates more accurate over time.
Direct service charge records from our property graph. When we have a verified record for a property, we return the exact value with full provenance and confidence metrics.
Machine learning models analyse real-time property events to calculate estimates from comparable units within the same building. The system processes 2-100+ comparables and learns from each new data point, continuously improving estimate accuracy as the property network expands.
When building-level data is insufficient, ML models analyse nearby comparable properties using embeddings for characteristic alignment. The system considers property attributes, building ownership patterns, and spatial proximity. This method is only activated when confidence thresholds are met, ensuring estimate quality.
Dataset grows automatically as property graph expands with new data events
Accuracy increases automatically as network learns from new property events
Analyzes up to 100+ units per building for highly accurate estimates
Every record includes accuracy confidence, data source, and calculation method
POST /v1/property/service-charge/estimate
Content-Type: application/json
x-api-key: your_api_key
{
"locationId": "LDIN-001234567890"
}
Response (28ms):
{
"success": true,
"data": {
"value": 3250,
"confidence": 94,
"source": "building_ml",
"details": {
"comparablesCount": 18,
"calculationMethod": "per_sqm",
"averagePerSqm": 45.2,
"buildingUnitsAnalysed": 18,
"accuracy": "87-95%"
}
}
}| Field | Type | Description |
|---|---|---|
| value | number | Annual service charge (£) |
| confidence | number | Confidence score (0-100) |
| source | string | Data source: exact_record | building_ml | spatial_ml |
| accuracy | string | Expected accuracy range based on source and confidence |
| comparablesCount | number | Number of comparable properties analysed (ML methods) |
| calculationMethod | string | per_sqm | per_bedroom | building_average |
| averagePerSqm | number | Average rate per square metre (£/sqm) |
| comparables | array | Sample comparable properties with anonymised details |
Instant service charge intelligence during due diligence and property transactions
Automated affordability assessments factoring ongoing leasehold costs
Enrich listings with accurate service charge data before viewings
Benchmark building charges against market comparables and identify outliers
Calculate accurate net rental yields and total cost of ownership
Build service charge intelligence into search and analysis tools via API