Underwriting Methodology

How Oliva scores Dubai property

Oliva produces an independent 0 to 100 quality rating for every Dubai off-plan project, the Oliva Score. It is the same number for every investor and cannot be influenced by developers. This page explains what the score measures, where the data comes from, and how it is computed.

What the Oliva Score measures

The Oliva Score is built from six differentiating dimensions. Macro context (interest rates, GDP, inflation, currency) is computed nightly and shown separately as Market Context, because macro factors move every Dubai project identically in a given quarter and so do not differentiate one project from another.

• Financial Value (22%): whether the price is attractive relative to the area, the income the property can generate, and the flexibility of the payment plan.
• Market Dynamics (20%): the health and momentum of the local market, read through transaction activity, supply and demand balance, and pricing trends.
• Location Quality (20%): amenity density, transit links, proximity to schools and healthcare, and sub-area premium.
• Developer Trust (15%): lifetime delivery history, years active, cycle resilience, and licensing standing.
• Risk Assessment (15%): price volatility, oversupply risk, and concentration of a single developer or unit type.
• Liquidity and Exit (8%): resale velocity, rental demand, and the health of the broader capital market.

Where our data comes from

Every data point that feeds the Oliva Score can be traced to an authoritative source.

• Dubai Land Department (DLD): the official registry for every real estate transaction in Dubai. Used for transaction prices, volumes, and area-level trends.
• RERA: the Real Estate Regulatory Agency within DLD. Used for project registration status, escrow compliance, and developer licensing.
• Ejari: Dubai's official rental contract registry. Used to validate rental demand and observed yields at the area level.
• RERA Mollak registry: the official registry for service charges and owner-association governance, reported per building.
• FRED (US Federal Reserve Economic Data): used for global macro signals including treasury yields and volatility indices that affect Gulf markets.
• Licensed market data providers: paid feeds for project-level detail, unit pricing, and payment plans, cross-referenced against DLD and RERA.

How the Score is computed

The scoring pipeline has four steps. We describe each step qualitatively; we do not publish exact coefficients or cutoffs.

Step 1. Normalization

We normalize raw data points so different metrics live on the same scale. A price per sqft and a rental yield cannot be added together directly. Normalization puts them on a common footing so dimensions can be aggregated consistently.

Step 2. Confidence weighting

Newer and more complete data matter more. Each input carries a confidence level reflecting freshness and coverage. A recent transaction near the project contributes more than a distant or stale one.

Step 3. Dimension aggregation

Within each dimension, the normalized and confidence-weighted inputs are combined into a single dimension score from 0 to 100.

Step 4. Overall Score

The six dimension scores are combined by their weights into a single Oliva Score from 0 to 100.

No paid placements

Developers cannot sponsor listings, cannot pay for higher rankings, and cannot influence their Oliva Score. The methodology is algorithmic. A project with weak fundamentals shows a weak score regardless of marketing spend.

What we publish, what we do not

We publish the framework, the six dimensions, and our data sources because you need to trust the score. We do not publish exact weights, sub-metric coefficients, or feature-engineering details, both to prevent gaming and to protect ongoing research that improves the score over time.

When we show limited data

Every section carries a confidence label. Limited data means we could not produce a number that met our own bar, so we did not produce one. We never show a derived number that was not actually computed from the project's own data. When new data arrives, the section fills in automatically on the next view.

Disclaimers

The Oliva Score is an analytical tool for comparing projects. It is not personalized investment advice and is not a recommendation to buy, sell, or hold any property. Government transaction data typically has a lag of one to two weeks. Areas with very few historical transactions carry lower confidence and are shown with a data confidence indicator. When we improve the scoring model we version it, and historical scores reflect the engine version active when they were computed. Always conduct your own due diligence and consult qualified advisors before investing.