Methodology
How BlockBrick analyses listings
Most property platforms keep their analysis a black box. BlockBrick publishes it. Every listing on Market Watch is assessed against the same criteria, and the result is a research signal — the BlockBrick Score (beta) — never investment advice.
Data quality
Each listing gets a 0–100 completeness score across the fields we track: price, location, source link, source identity, images, bedrooms and type, and a rental estimate. Missing fields are shown as missing — they are never guessed or filled in.
Source quality
We prefer listings with a named agency or provider and a verifiable link to the original listing. BlockBrick's sourcing is permission-first: images and data are only published where rights allow, and every import passes through a review queue before it appears publicly.
Price and locality context
We compare asking prices against what we know about the locality. Price-per-square-metre benchmarks for Maltese localities are being built up as verified floor-area data becomes available; until a listing has that data, no price-benchmark factor is scored for it.
Yield assumptions
Where a rental estimate exists we compute an estimated yield and compare it against the typical Maltese long-let range (internal estimate, roughly 3–5% net). When only a gross figure is available we derive an indicative net figure at 75% of gross to account for costs. Yields well above the typical range raise a verification flag, not a recommendation.
Restoration & grant-route relevance
Listings are checked for renovation-led signals: stated renovation need, Urban Conservation Area (UCA) indicators, houses of character, long-vacant or unconverted properties. This factor is deliberately capped until routes are verified on the ground — some Maltese schemes apply only to owner-occupiers or specific structures, so relevance is always 'to investigate', never 'grant secured'.
Human review
A person reviews every listing before it is highlighted. The review status — not reviewed, in review, shortlisted, or set aside — feeds directly into the score. AI and automation help the team ask better questions; they do not approve anything.
What the score will not do
- It will not tell you to buy or sell anything.
- It will not predict performance or guarantee returns.
- It will not replace legal, tax, planning or financial due diligence.
- It will not approve investments — people and processes do that.
BlockBrick Score (beta) is a research signal based on listing data, internal benchmarks and human review. Not financial advice, not a recommendation and not a prediction of performance.
Verifiable records, not crypto hype
In the future, BlockBrick may use blockchain in the background to make records easier to verify: timestamped documents, tamper-evident update histories and — subject to the final legal structure — auditable ownership records.
Users will not need crypto wallets, tokens or any blockchain knowledge. If permissioned record standards (such as ERC-3643-style eligibility-controlled tokens) are ever used, that choice follows the legal structure — not the other way around. No infrastructure will launch without legal and regulatory approval.
Why AI does not approve investments
Automated analysis is good at surfacing signals — an unusual price, a strong yield estimate, a possible UCA angle — and bad at judgement. Property decisions depend on legal title, planning constraints, building condition and dozens of local facts no model can verify from a listing page. That is why every BlockBrick score is framed for review, capped where data is unverified, and followed by human due diligence. The score exists to decide what deserves attention next, not what anyone should buy.