Real-time housing liquidity & demand intelligence—

Leading official price indices by ~2 quarters.

Live, privacy-safe indicators of price pressure, competition, and buyer-type demand. For regulators, banks, developers and funds making forward-looking decisions.

Signal lead

2-quarters ahead of CSO

Privacy

k-anonymity + differential privacy

Coverage

Production scale (growing)

Panoperty Index (indicative)

1,842.76

+2.4% Today (+43.12)

Offers Processed

€2.5B+ (Annually)

Markets

Ireland & US

What Panoperty Is

Real-time market intelligence that turns offer-level supply and demand behaviour into forward-looking, institutional-grade signals. Coverage grows; the core index leads official statistics by ~2 quarters, and the underlying heatmaps reveal competition and buyer-type shifts before they surface in lagged data.

We ingest live offer, bid and sale activity, apply privacy-preserving transformation, and surface price-pressure, liquidity, and demand segmentation in a secure API and automated report feed.

Institutional decisions—macroprudential policy, credit underwriting, development planning—depend on stale data. Panoperty replaces guesswork with a calibrated early signal backed by audit trails and governed methodology.

Key Data & Insights

Actionable, privacy-safe real estate intelligence delivered programmatically.

Panoperty Index

Composite, real-time price benchmark that leads lagging official data and can serve as a settlement/reference signal or derivative underlier.

Daily settlement-level signal
Lead indicator (~2 quarters ahead)
Benchmark-grade governance

Behavioral Demand

Real-time insight into competition dynamics and buyer intent: who is bidding, how often, and with what success profile.

Buyer-type mix (FTB / investor / trader-upper)
Attempts-before-success & bid velocity
Liquidity pressure (DOM, bids-per-listing)

Granular Analytics

Segmentation and imbalance detection across geography, property type, and price band for tactical and strategic decisions.

Localised heatmaps
Supply / demand divergence
Elasticity & pricing signals

Forecasting

Short-horizon forward price projections with confidence bands, enhancing stress tests and underwriting decisions.

1–4 quarter outlooks
Leading indicator integration
Scenario-adjusted outputs

API-First Delivery

Secure, versioned endpoints with authentication and throttling—plug into existing systems with minimal engineering lift.

Bearer token auth
Rate-limited & audited
Sandbox / production separation

Privacy & Security

Built for institutional trust: pseudonymisation, k-anonymity fallback, differential privacy, and audit trails guard against re-identification.

GDPR-compliant
Differential privacy budgeting
Hourly bucketing + suppression

Packages

Tiered licensing to match institutional use cases. Start with a pilot, scale to Pro, and lock exclusivity or high-frequency delivery where needed.

Research / Pilot

State bodies, think tanks. County-level index, quarterly PDF, basic heatmaps, fixed onboarding.

County aggregates
Quarterly narrative
Low-touch integration

Pro

Banks, developers, REITs. Full behavioural detail, buyer mix, monthly deliverables, forecasts.

Buyer-type heatmaps
Monthly index + forecast
Liquidity pressure metrics

Exclusive / HF

Funds, derivative partners. Hashed-ID enhancements, intraday ticks, regional exclusivity.

Intraday indication
Sector exclusivity
Enhanced alpha signals

Sandbox & Synthetic Data

Integrate and test without risk. The sandbox generates realistic, schema-compatible synthetic market data with configurable scenarios: normal, liquidity squeeze, investor surge, regional shifts.

Why use the sandbox

Full API schema parity with production (no real PII).
Scenario presets: demand spikes, supply droughts, buyer-type shifts.
Reproducible seeds for consistent integration testing.
Safe for internal model training, partner onboarding, and demoing.

Getting started

Request a sandbox key.
Pull sample endpoints; choose scenario.
Validate models or integration.
Swap to production token when ready; coverage upgrades sharpen accuracy.

Example request

GET /api/v1/index/PAN-IE
Authorization: Bearer <sandbox-key>

Example response

{
  "date":"2025-07-30",
  "value":1842.76,
  "lead_signal_quarters":1,
  "buyer_mix":{"FTB":72,"Investor":15,"TraderUpper":13},
  "over_ask_pp":7.4,
  "dom_days":56
}

Methodology & Accuracy

Transparent, governed construction. Real transaction behaviour feeds a composite index, enhanced by privacy-preserving techniques, delivering early signals with quantifiable error bounds.

Index Construction

Composite of over-ask, bids-per-listing, and days-on-market weighted to reflect price pressure and liquidity. Updated daily; settlement close published with audit trail.

Lead: ~1 quarter ahead of official CSO prices. Correlation r≈0.65; MAE ±1.7 pts today, improving with coverage.

Privacy & Governance

Pseudonymised IDs, k-anonymity with fallback & suppression, differential privacy budget tracking, hourly bucketing, and T+24h release to prevent re-identification.

Compliance: Designed for GDPR-safe use; benchmark-administration ready (EU BMR alignment).

Forecasting & Uplift

Short horizon forward projections integrate liquidity and behavioural signals. Improves credit underwriting and policy stress testing with confidence bands that tighten as coverage grows.

Empowering Decisions

Specific institutional use cases with measurable impact.

Central Banks & Governments

Early warning on overheating, real-time liquidity stress, calibrated policy levers with a forward-looking price signal.

Banks & Covered Bond Desks

Dynamic collateral valuation, better stress tests, adjusting haircuts using live demand and liquidity shifts.

Developers / REITs

Price optimisation, scheme-mix decisions, early detection of buyer-type shifts and competition intensity.

FAQ

How accurate is the index?

Is the data anonymised?

How do I integrate?