INSURANCE
Where does risk concentrate?
In the insurance sector, location data plays a critical role in accurate pricing, risk assessment and field organisation. Next Geo enables insurance companies to both direct their field teams more effectively and make data-driven decisions in processes from policy production to claims management.
THE QUESTION ON THE SECTORS PAGE
Where does risk concentrate, and where should the field team go?
Medium‑high
Low → Very high, five classes. This sample address sits in the second class from the top.
Classification is made at the address or neighbourhood level and feeds pricing and risk premium calculations.
Location-based risk assessment means faster decisions at the centre and smarter ones in the field. The question has two halves, and so does this page.
- 5ANALYSIS TITLES
- 3SOLUTION PAGES
- 2PRODUCT PAGES
All three numbers can be counted from this page: the five analysis titles below, and the three solution pages and two product pages they resolve into.
OUR OFFERED SOLUTIONS
Five analysis titles for insurance.
Each of the five resolves into a named Next Geo solution or product. The link at the right of each row goes straight to that page.
Risk: where does it concentrate?
Where your policies and candidate addresses concentrate on the map: which address falls in which risk class, and which region is building demand for which product.
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PRODUCT Point Report
Risk Zone Analysis
Risk classifications based on earthquake risk, building status, population density and past claim records are made at the address or neighbourhood level. This ensures more accurate pricing and risk premium calculations.
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PRODUCT Location Analysis Web
Policy Density and Distribution Analysis
The distribution of existing policies on the map is analysed; product penetration, service area density and potential customer clusters are visualised.
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SOLUTION Forecasting
Prediction with Artificial Intelligence
With regional data models, it is predicted in advance which regions may have demand for which product groups. Sales and campaign strategies are shaped according to these insights.
Field: where should it go?
In what order the loss-adjustment, sales and collection teams should go — and where the next branch or agency should open.
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SOLUTION Optimization
Location Optimization of Field Teams
Field planning of loss-adjustment, sales or collection teams is optimised with location-based data. Visit density, regional demand and accessibility of service points are analysed.
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SOLUTION Location and Area Selection
Branch and Agency Location Selection
Decision support is provided by analysing criteria such as regional competition, population structure, service need and traffic density for new agency openings or branch planning.
Risk and Field are a reading order, not a separate product family: all five titles run on the same data infrastructure.
SAMPLE OUTPUT
One address on file, one week ordered.
The first panel holds the four rows that produce the risk class shown above; the second is the visit order for the same portfolio. Both are outputs of the five analysis titles.
- Earthquake risk
- High
- Building status
- Mostly pre-2000
- Population density
- 24,800 per km²
- Past claims within 500 m
- 34 files
These four rows produce the risk class at the top of the page. The claims history is your own record; the remaining rows come from the attached layers.
| RANK | DISTRICT | PRIORITY | SCORE | OPEN FILES |
|---|---|---|---|---|
| 01 | Pendik | 88 | 14 | |
| 02 | Tuzla | 79 | 9 | |
| 03 | Çekmeköy | 71 | 6 | |
| 04 | Sancaktepe | 64 | 5 |
Priority comes out of visit density, regional demand and the accessibility of service points. Loss-adjustment, sales and collection teams plan the week in this order.
Sample output. The figures are illustrative. Real reports are produced from your own policy and claims records.
THREE ANALYSES AT DISTRICT SCALE
What shows up once you leave the single address?
The two panels are one address on file and one week in order. The same five titles also work at district scale: three of them take on, in turn, risk, policy distribution and where a new point should go. The three paragraphs below take those three titles in order, and the three frames follow the same order.
Risk Zone Analysis breaks the city into hexagonal cells, each cell gathering the claims history, building stock and environmental factors inside its own footprint into one value. The cells sit on a density scale that runs from low risk to very high; which step an address falls on is given in words in the panel at the top of the page.
Policy Density and Distribution Analysis places each district in one of three penetration bands: policy-dense, moderate, weak. The place to look is not the dense districts but the weak ones — where penetration is low, what is showing is the portfolio's gap, not its strength.
Branch and Agency Location Selection measures a candidate point with two catchment rings and counts the existing points standing around it. The scorecard for the candidate comes down to one number out of a hundred.
All three titles also appear in the five-row list above, and every row links to its own solution or product page.
HOW WE START
From policy addresses to a risk report.
Three steps. Behind each one is a named Next Geo solution or product — no unexplained layer in between.
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01
Addresses become points
Your policy, claims and loss-adjustment records arrive as free-text addresses; they are matched, deduplicated and verified. Until three spellings of the same building resolve to one point, everything said about that address is wrong too.
- Matching
- Enrichment
- Deduplication
- Verification
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02
Risk and demand layers are attached
Earthquake risk, building status and population density are attached to every point. The claims history is your own record and stays with you.
- Earthquake risk
- Building status
- Population
- Claims history
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03
The report, the ranking and the forecast come out
Addresses are classified by risk and districts are ranked by visit priority. Policy distribution goes onto the map, and the demand forecast is built on the same layers.
- Risk report
- Policy density map
- Field visit order
Who is it suitable for?
- Non-life insurance companies
- Life insurance & pension companies
- Field operations managing expertise & collection teams
- Broker and agency chains
- Digital insurance platforms
Policy and claims records reach the system as free-text addresses, so address data is always the first job; the field team can then see the ranking on site through the mobile app. If you also run a branch and agency network on the banking side, the same infrastructure is described there for branches and ATMs.
NEXT STEP
Let’s map your portfolio together.
Let us define which dataset and which analysis titles your insurance portfolio needs.