Methodology 1.12.6
Every value comes from a named public source, is placed in national context, carries its own confidence, and is stamped with the version that produced it. So you can trace it, cite it, and get the same answer when you check it again.
01 · The primitive
A signal is one measured attribute of a UK area, from a named source, placed in national context, time-stamped and confidence-rated. Scores, comparisons and forecasts are all built on top of signals.
The measurement itself, in its own unit, or empty with a reason when there is nothing solid to report.
Where the value sits against comparable areas, from 0 to 100, so a number means something on its own.
How solid the number is, based on the source, the sample and how recent it is. Honest, not aspirational.
The named public dataset it came from, so you can cite it and stand behind it.
The methodology version that produced it, so you can see exactly which release a number came from and what has changed since.
One signal, with every part on show. Nothing is a bare number.
02 · Where the data comes from
Crime, deprivation, property, schools, amenities, transport and environment, each from official, public datasets. We name every one here, and every response carries its source and period alongside the value, so you can always show your working.
police.uk, the Home Office and Police Scotland. England · Wales · Scotland.
IMD 2025, WIMD and SIMD. England · Wales · Scotland.
ONS HPSSA and HM Land Registry. England · Wales.
Ofsted, within 1.5km and within 1km. England.
OpenStreetMap. Great Britain.
NaPTAN. Great Britain.
Environment Agency, Natural Resources Wales and SEPA. England · Wales · Scotland.
Postcodes are resolved to neighbourhoods through the official ONS spine, so every value lands on the right area.
03 · National context
Every value is ranked against comparable areas. Each country is ranked within itself, because their deprivation indices are built differently and are not comparable across the border. You can also rank an area against its own region, so a strong area in a quieter part of the country is not flattened by the national picture.
National ranking · median price, England
Westminster
Merton
Camden
Kensington and Chelsea
Barnet
Regional ranking · top of each region
Westminster · London
Elmbridge · South East
Hertsmere · East of England
Bristol · South West
Northumberland · North East
The same signal, the same country, the same shortlist. National returns five slices of prime London; regional returns the top of five different regions.
04 · Historical snapshots
Each month we add a fresh snapshot of every signal in every area, stamped with the period it describes and the date we recorded it. When a publisher revises an earlier period, the revision is recorded against that period, so the record stays true to the source and you can tell a late publication from a real change.
Every value carries the period it describes and the date we recorded it, so you can tell a late publication from a real change.
A figure you cite today names its source, its period and the methodology version that produced it, so anyone can check where it came from.
The record gets deeper every month, building up area history that nobody can backfill after the fact.
05 · Scoring
A score turns an area's signals into a single number from 0 to 100. Every profile scores the same seven categories; the profile only changes how they are weighted for its job. The scoring is deterministic: the same inputs on the same methodology version always return the same score.
How liveable an area is for a household. Crime, affordability and schools carry 20 each, transport 15, amenities and deprivation 10, environment 5.
Where to open. Amenities 25, transport 20, spending power, commercial costs and environment 15 each, crime and schools 5.
What an area looks like as an asset. Property 30, amenities, transport and environment 15 each, crime and deprivation 10, schools 5.
A balanced read for analysis. Crime and deprivation 15, every other category 14.
You can re-weight the seven categories for a single request, or save a weighting against your organisation and reuse it. Every score is stamped with the version that produced it, so you can trace the result to the published methodology and changelog.
06 · Beyond a single reading
As well as today's numbers, we work out how areas are changing, how they compare with their peers, and where a signal is heading. Each one comes with its own time window and its own confidence.
How crime and prices have moved against a year ago, on calendar windows.
Crime over the last six months against the six before, so a fast-moving area shows up early.
The two-year direction of monthly crime, steadier than a single jump.
How an area reads against similar areas, high or low for its kind.
The areas most like a given one, based on how closely they sit across the signals they share. A simple, symmetric similarity.
Areas that stand out from their peer group on a signal, so unusual places surface on their own. Worked out ahead of time, so it is fast.
A straightforward projection of where a monthly signal is heading, with a confidence band around it. A transparent trend, not a black box.
07 · Ask a question
Ask a question in plain English and it is turned into a precise query. You get the answer and the exact query behind it, so every result can be reviewed and run again. Prefer to be exact? Send the typed query yourself and skip the AI entirely.
Your question, in plain English
English neighbourhoods under £250k where prices are rising, crime is below average and deprivation is low, best growth first, top five.
Understood as
Rank English areas, keep the ones under £250k with prices rising, crime and deprivation both in the better half, sort by growth, return the top five, and hand back the plan so you can run it again.
08 · Confidence
Every value comes with a confidence level and a short, plain-English reason. It reflects how fresh the data is, how large the sample is, whether we had to fall back to another source, and how much the signal moves around. When the data is thin, the response says so.
Fresh data from the primary source, a healthy sample, little movement. For example: Recent crime, or prices where there are plenty of sales.
An older release, a smaller sample, a fallback source, or a more volatile signal. For example: Older deprivation indices, or prices in a thinner market.
A proxy fallback, or very little underlying data. For example: Prices where there are very few recent sales.
No usable data. The value comes back empty, with the reason. For example: A source is down, or the area is outside our coverage.
Categories that are inferred rather than directly measured are capped at medium confidence by design. And when we watch an area for change, a move backed by too little data is held back rather than flagged, so a one-off blip never triggers a false alarm.
09 · Versioning
Every response carries the methodology version that produced it, and every release is published in the changelog with what it changed. When a release moves a number, Monitor says so: each change in a watched portfolio states whether the area moved or our method did.
A change to what a score means, such as a new dimension or a new way of ranking.
A new signal, source or capability, or a better way of reading one that already exists.
A correction to a loader, a count or a reason.
Every release, whatever its size, is listed in the changelog with the figures it moved. A watched portfolio keeps the values it held at each period, so a change caused by a release shows up in the feed as a method change, never as a move in the area.
Version history
Deprivation is served by domain, with each nation's published rank and score, ranked within the nation; Wales moves to WIMD 2025 on 2021 neighbourhoods; Scotland is read from the published SIMD 2020v2 file; and any deprivation ranking names its nation. Each nation's deprivation index is stored and served as 13 decile signals by domain: income, employment, health and education in England, Wales and Scotland, crime in England and Scotland, and each nation's own further domains. A domain carries the published rank and, where the publisher gives one, the score; Scotland publishes no score. Percentiles rank an area within its own nation. Wales is read from WIMD 2025 (1,917 neighbourhoods on 2021 boundaries) in place of WIMD 2019 (1,909 on 2011 boundaries, remapped). Welsh deciles and ranks change with the edition, and explanations rank a Welsh area out of 1,917. Scotland is read from the Scottish Government's published SIMD 2020v2 file, with ranks and deciles exactly as published, in place of the ArcGIS service. Ranking areas by any deprivation signal, including deprivation.imd_decile and deprivation.imd_rank, needs a country or a local authority, because deciles and ranks are relative within each nation.
England's flood counts are rebuilt by a committed, checked generator with the Environment Agency's own 3km rule, so stored and live counts agree, and the Environment score ranks flood exposure among the nation's neighbourhoods instead of taking a fixed amount off per flood area. A flood area counts when the box around its outline, in British National Grid metres, overlaps the 6km square centred on the neighbourhood, the rule of the Environment Agency's dist=3 query. The stored counts matched the live query at 199 of 200 sampled English neighbourhoods; the other sits 0.2m inside the edge. The flood area list and outlines were retrieved on 5 October 2026 (4,208 areas). The average English neighbourhood now has 8.2 flood areas within 3km, against 2.4 in the August file, and neighbourhoods with none fall from 8,871 to 21. The August file under-counted and its method was not recorded. Environment ranks flood exposure among the nation's neighbourhoods measured the same way, the least exposed highest: England by the Environment Agency count, Scotland by SEPA's maps, Wales by NRW's. It uses the 5 to 95 scale of the other ranked dimensions; active warnings and parks adjust it as before. Before, each flood area took 6 points off, and 45% of English neighbourhoods scored the maximum 95; with the corrected counts the same rule would have moved the English average from 87 to 57. Ranked, the English average is 59 and 11% reach 95.
The OpenStreetMap amenity counts are rebuilt by a committed, checked generator from the Great Britain extract of 3 October 2026, with the live query's rules: a park or school drawn as an outline counts when its edge is in reach, and gardens and swimming pools count only when named. Station and bus stop counts are unchanged. A school, park or other place mapped as an outline counts when any part of it is within the category's radius, as the live OpenStreetMap query does. Before, the stored counts came from an offline file whose method was not recorded. Gardens and swimming pools count towards parks and leisure only when named, in the stored counts and the live query. In Great Britain 339,008 of 343,813 gardens and 22,681 of 23,166 swimming pools are unnamed, almost all private. Against the August 2026 counts: restaurants, pubs, healthcare and shops move by at most 1.3% nationally, schools rise 8.8% and parks and leisure 8.5%. Highlights name the nearest stations, hospitals and surgeries, supermarkets, schools, parks and pubs from OpenStreetMap, and the counts are dated by the extract's day.
A postcode our records do not hold yet takes its neighbourhood's official area type; one with no known type is ranked among all GB neighbourhoods and says so, instead of being treated as suburban. Scores for every other postcode are unchanged. A valid postcode missing from the postcode spine, such as a newly issued one, takes the band most of its neighbourhood's postcodes carry, the rule a neighbourhood reached by its code already follows. Where no band can be found, area_type and rural_urban are null and transport, schools and amenities rank among every banded GB neighbourhood, the three band distributions merged by count. Each of their confidence reasons says so, and the score's reference is national (GB, area_type_unavailable). Before, such a postcode was ranked as suburban without saying so. The score history the rescore job writes stores a null area type for such a postcode instead of suburban.
In England, a score made without Ofsted data (a key whose bundle leaves schools out, or a failed lookup) scores the Schools dimension at the neutral midpoint with no confidence, instead of as an area with no graded school nearby. Every scheduled source load is now judged by a quality gate before it is published. Before, no Ofsted data was read as no graded school within 1.5km, which ranked the Schools dimension near the bottom (2nd percentile in our reference case) and lowered the overall score. A neighbourhood with no school in range still scores as before. The schools figures say the Ofsted request failed when it did, and give measured zeros where Ofsted's register holds no school in range. A SEPA flood reply without a count is treated as a failed request, never as no flood map. Every scheduled source loader accounts for each row it reads and is judged before publishing: a load that is incomplete, out of date or changed in shape is refused and the previous values stay served.
No street-level crime is stored or served for Gloucestershire, whose police force has published nothing to police.uk since January 2026; its council-area figure is shown instead, as for Greater Manchester. House prices and sales move to ONS's year ending March 2026. police.uk holds no Gloucestershire Constabulary data after January 2026, so seven of the twelve months counted for Gloucestershire's 393 neighbourhoods were empty and they ranked among the lowest-crime in the country. Their street-level crime, ranks, trends and history are removed, the crime figures give the coverage-gap reason, and the Home Office council-area rate (year ending March 2024) is shown as context, never scored. Median house price, its change on the year before and the sales count are ONS's year ending March 2026 edition (released 17 September 2026), replacing year ending September 2025; the sales count covers April 2025 to March 2026.
Every value states, as calendar dates, the period it describes, whether the source gave that date or it is the day the value entered OneGoodArea, and when it was loaded or fetched. Clients can order signals by those dates. Values and scores are unchanged. Every signal carries period (start and end dates), period_basis (reference or load), loaded_at and, for a value fetched live, retrieved_at. observed_period is now written from the period as YYYY-MM-DD or YYYY-MM-DD to YYYY-MM-DD. GET /v1/area and /v1/signals/:category take sort=period, loaded or released to list signals newest first by that date. Ranked areas keep value order and carry each value's dates. History is keyed by the date each period ends, so a value that changes keeps both points: amenity counts that changed on 24 September 2026 now have their own history entry. Method words such as Precomputed and Live query no longer appear as periods.
Crime is counted over the same twelve calendar months for every neighbourhood, and Greater Manchester is no longer ranked on the few stray street-level records police.uk holds for it. Crime scores move only for quiet neighbourhoods whose count had reached back beyond a year. Every crime total, rate and type count covers the twelve calendar months ending at police.uk's latest month, a month with no crime counting as zero. Before, a quiet neighbourhood's window stretched back over earlier months to make up twelve. No street-level crime is stored for Greater Manchester, whose police force has not published to police.uk since July 2019. Its few stray records had ranked its neighbourhoods as the lowest-crime in the country in rankings and similar places. Its council-area figure is unchanged. A neighbourhood that drops out of a crime load loses its old totals instead of keeping them.
A crime type with no recorded crimes reads 0 instead of missing, every recorded crime is counted in a type, and the crime score gives the same reason for missing data as the figures do. Scores are unchanged. Every crime type is stored for every neighbourhood with recorded crime, 0 where none occurred. Before, a type with no crimes had no row and was served as not published, beside a reason describing a robust sample. Other crime, the fourteenth police.uk type, is counted, so the types add up to the total. Where street-level crime is missing, the Crime dimension of the score gives the same reason as the crime figures (a force that stopped publishing, a nation police.uk does not cover, or a failed request) and says it was scored at the neutral midpoint.
Percentiles place tied values in the middle of their group, the rule scores already use, so the best value on a skewed signal no longer reads as middling. Scores are unchanged. Every percentile and normalized value is the mid-rank: the share of areas below the value plus half the share equal to it. Before, tied values took the share below them, so the half of ranked neighbourhoods where every school is Good or Outstanding sat at the 49th percentile and deprivation decile 10 stopped at the 90th. They now read at the 74th and 95th. Values shared by no other area move by at most half an area's share. Similar places are rebuilt on the new positions.
Crime trends are measured over exact calendar months, every property figure describes the same year, and four neighbourhood property trends built on too few sales or on unfinished Land Registry months are retired. Scores are unchanged. Crime trends (the change over a year, over six months, and the 24-month trend) cover whole calendar months ending at police.uk's latest month, and a month with no recorded crime counts as zero. Before, a trend used the latest months an area had rows for, so a quiet month stretched the window back and some areas got no trend at all. Retired: the neighbourhood price change over a year and over six months, built from as few as ten sales and able to contradict the official ONS change, and the sales-volume change and trend, biased low by the months Land Registry is still registering. property.price_change_pct, the official ONS change, is the price trend. property.transaction_count is the Land Registry sales in the same year as the ONS median (the year ending September 2025), so every property figure describes the same twelve months. Before, it counted this year's sales registered so far. A derived value is removed when an area stops qualifying, and every derived signal names the one question it answers; no two public signals may answer the same one. Similar places are matched without the retired signals, and never on the values computed from similar places themselves. Crime types carry their official police.uk names on every surface, transport credits NaPTAN, and every served period and count reads in words.
Property confidence follows the sales behind the median itself, and every score explanation names where its figures come from and reads as plain sentences. Scores are unchanged. Where the property median is the ONS rolling-year figure for the neighbourhood group, the Property dimension's confidence follows that group's sales in the year, as the signal's own confidence does. Before, it followed the recent Land Registry sales in the postcode district, so a well-evidenced median could read low. Property reasoning names the basis of the median (the ONS figure for the neighbourhood group, or the recent sales in a postcode district) and credits ONS or HM Land Registry to match. A missing prior-year median is left out instead of printed as undefined. Explanations join their facts with semicolons and full sentences, use "an" before a vowel, and never show an empty label. A test in CI holds every explanation to these rules across every preset, band, nation and data path.
Peers must share most of an area's signals, and each area's stored peer set is replaced at every recompute, so the signals that compare an area with its peers use the right peers. A peer must carry at least 75% of the target's signals. Before, sharing 3 was enough, so an area could match others that were alike on only a few signals. Each neighbourhood's stored peer set is replaced when it is recomputed instead of growing, and the peer-relative signals read only the ranked 20 peers.
Scotland and Wales flood risk is measured once per neighbourhood and served from the store, like England, and every flood figure names its agency and what it measures. Scotland (SEPA) and Wales (Natural Resources Wales) flood risk is measured at each neighbourhood's centre, quarterly, instead of at the postcode on every request. Scottish and Welsh flood figures, and the Environment scores built on them, can move as a result. The flood figure and the Environment reasoning name the agency and its measure: Environment Agency flood areas within 3km, or how many of SEPA's 6 or Natural Resources Wales's 3 flood maps lie within 250m. Active flood warnings are shown only when they were checked for the response; otherwise they are null and marked not included, never a zero.
Schools confidence now accounts for the schools in range that carry no grade and for how old the grades are, and every schools figure states the span of inspections behind it. Confidence drops one band when fewer than three in four schools within 1.5km carry a grade, and one band when the median grade is more than six years old. The reason names each step. Every school in range is counted (schools.total_count), and an area whose schools are all ungraded reads zero graded with an unknown share instead of no schools. schools.median_grade_age_years gives the median age of the grades. The period reads as the span of the grades (for example "Inspections Mar 2019 to Jun 2026") instead of "Latest inspections". Scores and counts are unchanged.
Transport, schools and amenities are scored by where an area ranks among neighbourhoods of the same kind (urban, suburban or rural), from reference distributions rebuilt at every refresh, instead of hand-set benchmarks. Each input is ranked among every GB neighbourhood of the area's band (mid-rank percentile), and the dimension is 5 + 90 times the weighted mean rank. A 70 is better served than about 70% of similar places, and the reasoning states the rank. Before, fixed benchmarks put about half of urban neighbourhoods at the top score for schools and amenities, so those scores could not tell city areas apart. Typical areas now sit near 50. Schools rank England on the quality-weighted graded count and Wales and Scotland on the school count. Amenities count school facilities from OpenStreetMap in every nation. Confidence rules and the other dimensions are unchanged.
Every state-funded school in England is counted again, with a current grade from its most recent Ofsted judgement, now that Ofsted gives no overall grade. Before, only schools holding an old overall grade were counted, about half of them. A school's grade comes from the most recent inspection that names one: a report card's curriculum and teaching grade, the overall effectiveness or, where it is not judged, the quality of education, or an ungraded inspection that confirms the grade. Schools with a grade rise from 9,775 to 19,897 of 21,957; the median neighbourhood has 7 graded schools within 1.5km, up from 3. Schools and amenities scores rise where schools were missing. Schools with no judgement are listed by /v1/area/schools, and every listed school names the judgement its grade comes from (grade_source).
Transport scores no longer fall as an area gains rail and underground stations: stations add points with diminishing returns up to five and level off after, as the engine was designed to. Before, every station past the first took points away with no limit, so from the sixth station the transport score fell: central Manchester, with 18 stations within 2km, scored lower on stations than a place with five. Areas with five stations or fewer are unchanged. About 3,200 neighbourhoods with more than five, nearly all in the major cities, score higher. No signal value changes.
Every area is benchmarked as urban, suburban or rural from the official rural-urban classification of its postcode again, so transport, schools and amenities are judged against what is normal for that kind of place. The area type comes from the official rural-urban classifications, read per postcode from the ONS Postcode Directory. England and Wales: rural where the 2021 Rural Urban Classification says rural; urban where it says urban and the postcode lies in a conurbation of the 2011 classification, the split the 2021 classification no longer publishes; every other urban postcode is suburban. Scotland: the Scottish Government Urban Rural Classification, with large urban areas urban, other urban areas suburban and settlements under 10,000 rural. Before, the classification could not be read and every area was benchmarked as suburban. Scores move for urban and rural areas; suburban areas are unchanged. rural_urban on the area response carries the name of the class that decided the band. No signal value changes.
Schools confidence now follows the number of inspected schools behind the figures, on one ladder shared by the store, the area profile and the score, and a share of Good or Outstanding is ranked only where at least three inspected schools stand behind it. Schools confidence is 0.9 with six or more inspected schools within 1.5km, 0.6 with three to five, and 0.4 with one or two; the reason names the count and the band. Before, every area read 0.9 regardless. schools.good_or_outstanding_pct carries a national and regional percentile only where at least three schools are inspected; with one or two the share is served without a rank, and those areas leave the ranked distribution. The scored schools dimension uses the same ladder: high confidence at six or more inspected schools, medium at three to five, low below. No value changes: every count and share is exactly as before.
The population behind the per-resident crime rate is now served as its own signal, dated to the census, so total, population and census year are three explicit fields and the rate can be reproduced or re-based from them. New signal crime.population: usual residents of each neighbourhood from Census 2021 on 2021 boundaries, the denominator of crime.rate_per_1000. No value changes: the rate, the count and every other signal are unchanged.
Crime now carries a per-resident rate beside the raw count: recorded crimes per 1,000 usual residents over the trailing twelve months, from the Census 2021 population of each neighbourhood. A raw count is not comparable across areas, because a dense neighbourhood always reads higher; the rate is, and it carries its own national percentile. The count, the monthly figure and the scored crime dimension are unchanged. New signal crime.rate_per_1000: recorded crimes per 1,000 usual residents over the trailing twelve months, England and Wales, with a national percentile. The denominator is the Census 2021 usual-resident count for each 2021 neighbourhood, committed with the code and stated in every reason. The rate is only produced for a full twelve-month window; a shorter window is never annualised. Where street-level crime is not published (Greater Manchester) the rate is withheld with the count, and the council-level figure remains the context.
The property median and its year-on-year change now come from the ONS rolling-year series for the neighbourhood group (MSOA) an area belongs to, the small-area series ONS still publishes. Every neighbourhood carries its group's figure with provenance saying so, and confidence follows the group's own sales for the year. No neighbourhood-level trend is surfaced from fewer than ten sales. The Land Registry transaction count keeps its own window. Median price and year-on-year change are the ONS rolling-year figures for the area's MSOA (year ending September 2025 edition), inherited by every neighbourhood in the group; the neighbourhood-level series ONS discontinued at year ending March 2023 is retired. Confidence on the median and the change follows the MSOA's own sales in the year on the same ladder used for Land Registry counts, so an inherited figure never reads more certain than its sample. Any trend derived from neighbourhood-level sales, in the store or on the live fallback, requires at least ten sales in each window before it is surfaced. The transaction count carries its own period rather than the median's, and the live postcode-district fallback names its grain.
Amenity and transport signals now serve from a precomputed store instead of a live query. Transport access points (rail, metro and bus stops) are sourced from NaPTAN, the national public transport access node register, replacing crowd-sourced OpenStreetMap stops with complete official coverage. Amenity category counts come from a committed OpenStreetMap extract. Both are precomputed per small area, so values are stable and no longer depend on a third-party query at request time. Transport access points (stations and bus stops) now come from NaPTAN, the official national register, giving complete and consistent coverage in place of crowd-sourced OpenStreetMap stops. Amenity counts (schools, food and drink, healthcare, shops, parks and leisure) are served from a precomputed OpenStreetMap extract rather than a live query, removing request-time variability. Counts are precomputed per small area across England, Wales and Scotland, matching the previous per-category search radii so scores stay comparable.
Property prices now come from ONS House Price Statistics for Small Areas (HPSSA), a rolling-year median by small area, instead of a self-computed Land Registry window median. This removes thin-sample noise, so a single recent sale no longer swings an area's price or its year-on-year change; transaction volume still comes from HM Land Registry. Property median price and year-on-year change are now sourced from ONS HPSSA (rolling-year median by LSOA), so small areas with few recent sales no longer show volatile figures. Transaction count continues to come from HM Land Registry Price Paid Data. HPSSA is remapped from 2011 to 2021 small-area boundaries to match the current geography (a 2021 split inherits its parent's figure, a merge takes the mean of its parents).
Intent-aware scoring. Every preset now scores the same seven categories (safety & crime, deprivation, property, schools, amenities, transport, environment) using the full source set; intent changes only how those categories are weighted. Seven standard dimensions for every preset (safety & crime, deprivation, property, schools, amenities, transport, environment), replacing the previous five-dimension-per-preset sets. Intent-aware weighting: the same category contributes differently by decision type (property weighs more for investing, transport for business, deprivation for moving). Business and investing presets now score directly from property and schools signals instead of derived demand proxies. Custom weights let you re-weight the same seven categories for any preset.
Deterministic UK area-intelligence engine. Four decision presets, five weighted dimensions each, per-dimension confidence, and full source attribution. Scores are computed from public data by fixed formulas; no AI in the scoring path. Deterministic scoring: the same inputs and engine version always produce the same score, with no AI in the scoring path. Four decision presets (moving, business, investing, research), each weighting the categories for its use case. Area-type benchmarks (urban, suburban, rural) so scores are fair across settlement types. A confidence level and a plain-language reason on every value, so you always know how solid each number is. Seven signal categories from public data: crime, deprivation, property, schools, amenities, transport, environment. Every value carries its source and observed period. Normalised values plus national and regional context for cross-area comparison. The engine version is stamped on every response so reviewers can identify the methodology that produced it.
10 · For your team
Levers are the controls that shape the API for your keys. All three are opt-in, so if you leave them alone everything works exactly as it does by default. Role-based access, white-labelling and IP allowlisting sit alongside them.
Choose which signals your team's keys can see, so everyone works from the same agreed set.
Save a scoring weighting for your organisation and reuse it across the team, so every score is worked out the same way.
Define your own set of areas, so similar areas means similar within your portfolio, not the whole country.
11 · Scope and limits
Said up front to save you time. This is decision-grade area screening and analysis. It is not valuation, not lending, and not address-level today.
It does not predict the market value of a specific property. Use a dedicated AVM for that.
It is an input to enrich your own models, never a decision on any individual's affordability or creditworthiness.
We score small areas, not individual addresses. For a specific property, pair us with an address-level source.
An area right on the boundary of another deserves a closer look. These boundaries are administrative, not behavioural.
Deprivation correlates with protected characteristics. In regulated workflows, buyers stay responsible for fair-lending compliance.
Source-backed, placed in context, confidence-rated and version-stamped. Everything a team needs to build on UK area data with confidence.