Not how many you hold.
What share of the market.

Load your customer book and ALR measures it against the market around it. It may hold half a million mortgages, a national policy book, a loyalty base in the millions, every record geocoded and set against the households in its own neighbourhood.

Market sharePenetrationWhite spaceBook concentrationSegmentationBroker channelDaily refresh
The measure nobody else can give you

Penetration, not just presence

Knowing you hold 3 200 customers in a suburb, like Moreleta Park, means very little on its own. Knowing there are 8 400 residential properties there, and that 5 800 of them sit in the bands you actually serve, turns that number into market share, at neighbourhood level and nationally.

Riskscape holds the denominator

Households, income bands, property values and life stage for every neighbourhood in the country, built from the pixel up. Your book supplies the numerator. The result is a share-of-market read no customer list can produce on its own.
Neighbourhood 79910100 · 177 properties · 30 customers · 17% penetrationNeighbourhood 79910102 · 138 properties · 24 customers · 17% penetrationNeighbourhood 79910103 · 95 properties · 7 customers · 7% penetrationNeighbourhood 79910104 · 84 properties · 13 customers · 15% penetrationNeighbourhood 79910105 · 115 properties · 15 customers · 13% penetrationNeighbourhood 79910106 · 191 properties · 21 customers · 11% penetrationNeighbourhood 79910107 · 135 properties · 25 customers · 19% penetrationNeighbourhood 79910108 · 130 properties · 43 customers · 33% penetrationNeighbourhood 79910109 · 156 properties · 20 customers · 13% penetrationNeighbourhood 79910110 · 183 properties · 52 customers · 28% penetrationNeighbourhood 79910111 · 167 properties · 0 customers · 0% penetrationNeighbourhood 79910112 · 135 properties · 26 customers · 19% penetrationNeighbourhood 79910115 · 0 properties · 0 customers · n/a penetrationNeighbourhood 79910119 · 0 properties · 0 customers · n/a penetrationNeighbourhood 79910538 · 167 properties · 17 customers · 10% penetrationNeighbourhood 79910548 · 179 properties · 54 customers · 30% penetrationNeighbourhood 79910565 · 121 properties · 53 customers · 44% penetrationNeighbourhood 79910570 · 150 properties · 48 customers · 32% penetrationNeighbourhood 79910885 · 136 properties · 57 customers · 42% penetrationNeighbourhood 79910886 · 183 properties · 38 customers · 21% penetrationNeighbourhood 79910887 · 152 properties · 26 customers · 17% penetrationNeighbourhood 79910888 · 167 properties · 17 customers · 10% penetrationNeighbourhood 79910889 · 140 properties · 40 customers · 29% penetrationNeighbourhood 79910890 · 142 properties · 25 customers · 18% penetrationNeighbourhood 79910891 · 102 properties · 4 customers · 4% penetrationNeighbourhood 79910892 · 102 properties · 17 customers · 17% penetrationNeighbourhood 79910893 · 170 properties · 30 customers · 18% penetrationNeighbourhood 79910894 · 117 properties · 38 customers · 32% penetrationNeighbourhood 79910895 · 148 properties · 14 customers · 9% penetrationNeighbourhood 79910896 · 162 properties · 50 customers · 31% penetrationNeighbourhood 79910897 · 159 properties · 37 customers · 23% penetrationNeighbourhood 79910898 · 134 properties · 32 customers · 24% penetrationNeighbourhood 79910899 · 136 properties · 24 customers · 18% penetrationNeighbourhood 79910900 · 161 properties · 45 customers · 28% penetrationNeighbourhood 79910901 · 165 properties · 0 customers · 0% penetrationNeighbourhood 79910902 · 153 properties · 49 customers · 32% penetrationNeighbourhood 79910903 · 123 properties · 23 customers · 19% penetrationNeighbourhood 79910904 · 126 properties · 39 customers · 31% penetrationNeighbourhood 79910905 · 154 properties · 0 customers · 0% penetrationNeighbourhood 79910906 · 134 properties · 58 customers · 43% penetrationNeighbourhood 79910907 · 169 properties · 0 customers · 0% penetrationNeighbourhood 79910908 · 98 properties · 9 customers · 9% penetrationNeighbourhood 79910909 · 173 properties · 27 customers · 16% penetrationNeighbourhood 79910910 · 166 properties · 46 customers · 28% penetrationNeighbourhood 79910911 · 121 properties · 11 customers · 9% penetrationNeighbourhood 79910912 · 172 properties · 31 customers · 18% penetrationNeighbourhood 79910917 · 146 properties · 70 customers · 48% penetrationNeighbourhood 79910918 · 132 properties · 53 customers · 40% penetrationNeighbourhood 79910919 · 155 properties · 34 customers · 22% penetrationNeighbourhood 79910920 · 116 properties · 14 customers · 12% penetrationNeighbourhood 79911165 · 146 properties · 17 customers · 12% penetrationNeighbourhood 79911166 · 141 properties · 24 customers · 17% penetrationNeighbourhood 79911167 · 183 properties · 26 customers · 14% penetrationNeighbourhood 79911168 · 114 properties · 18 customers · 16% penetrationNeighbourhood 79911322 · 127 properties · 4 customers · 3% penetrationNeighbourhood 79911323 · 116 properties · 17 customers · 15% penetrationNeighbourhood 79911324 · 117 properties · 44 customers · 38% penetrationNeighbourhood 79911325 · 133 properties · 26 customers · 20% penetrationNeighbourhood 79911326 · 0 properties · 0 customers · n/a penetrationNeighbourhood 79911327 · 116 properties · 19 customers · 16% penetrationNeighbourhood 79911328 · 140 properties · 54 customers · 39% penetrationNeighbourhood 79911329 · 149 properties · 66 customers · 44% penetrationWhite space · neighbourhood 79910111 · 167 properties · no customersWhite space · neighbourhood 79910901 · 165 properties · no customersWhite space · neighbourhood 79910905 · 154 properties · no customersWhite space · neighbourhood 79910907 · 169 properties · no customersMORELETA PARK1 KM
LowHigh penetrationWhite space (profile matches, no customers)No residential properties
Moreleta Park, City of Tshwane - real neighbourhood boundaries and property counts (8 419 residential properties); the customer book is illustrative.
Share

Penetration by neighbourhood

Your customers as a share of the households that match your profile, at every grain from neighbourhood to province.
Opportunity

White space

Neighbourhoods that look exactly like the areas your best customers live in, where you hold nobody.
Exposure

Book concentration

How much of the book sits inside one flood zone, one fire zone or one catchment, with your own limits applied to it.
Profile

Segmentation without a survey

Income band, property value, title type, settlement character and life stage inferred from the address, for customers who have told you nothing beyond where they live.
Distribution

Book against network

Where your customers are dense and your branches, stores or ATMs are not. It also shows where a site serves nobody.
Movement

A book that moves

Customers relocate, areas gain and lose. Re-run the book on the same basis and the change is measurable rather than anecdotal.
Who uses it

Two books. One measure.

The same penetration read serves an insurer's policy book and a retailer's loyalty base.

Banks, short-term and life insurers

  • Mortgage book exposure by flood, fire and hazard band
  • Policy accumulation inside a single event footprint
  • Which areas the book is growing in, and which it is leaving
  • Customer density measured against branch and ATM coverage
  • Collateral quality by area, not by declared value alone
  • Portfolio segmentation for pricing and campaign targeting
  • The same view extended to the broker channel, scoped per brokerage

Retail and franchise networks

  • Loyalty base mapped to neighbourhood, live
  • Share of the catchment you actually hold, store by store
  • Which stores draw from where, giving real catchments rather than radii
  • Overlap between stores, measured from customer origin
  • Where a new store would find customers rather than steal them
  • Suburbs that match your strongest trade areas and hold no members
Channel

Give the same view to your brokers

An insurer's book arrives through brokers. Expose ALR to the broker network, scoped so each brokerage sees only its own clients. The risk conversation then moves to the front of the process, where it is still cheap to have.

01
Broker screens

Before the quote is promised

The broker enters an address and gets flood, fire, crime, emergency access and property detail back immediately, while the client is still on the phone.

02
Appetite applied

Your rules travel with the view

Hazard band limits, concentration caps and referral triggers are set by you. The broker sees that a risk falls outside appetite before submitting it, not three days later.

03
Underwriter receives

A clean, scored submission

Geocoded, confidence-graded and carrying the same figures the underwriter will see. No re-keying, no disputed addresses, no argument about whose flood map is right.

In the process

  • Fewer referrals and fewer declines late in the process
  • Submission quality improves before it reaches underwriting
  • One version of the risk, shared by broker and insurer

In the channel

  • Brokers manage their own book, covering renewals, penetration and growth
  • The insurer sees channel performance by area and by brokerage
  • Appetite is communicated by the tool rather than by circular

Scoped access. Each brokerage sees only its own book - the insurer sees the whole channel - one model, one version, one set of numbers.

POPIA

Handled properly.

Customer books are personal information under POPIA. Riskscape acts as an operator, processing on your behalf under written mandate.

What is kept, and what never is

What is stored
The location, an opaque reference of your own, and only the attributes an enabled function requires. No names, identity numbers, contact details, account or policy numbers.
Only what is needed
Penetration and white space need neighbourhood counts, not addresses. Concentration and pre-bind testing need locations and totals, not identities. Where a function does not need the point, the point is not kept.
Your data stays yours
Per-tenant separation, contractual deletion on termination, and area-grain output that is aggregate and falls outside personal information.

Our full data-handling position is available on request. It covers the treatment of each line of business and the controls behind it. We are happy to work through a privacy impact assessment with your team before any data moves.

Send us an extract.

A de-identified sample of the book is enough, being addresses and a reference. We will map it, measure penetration against the market around it, and show you the white space before the call.