Each topic below explains the evidence, the business problem it creates, how GLOBEIR solves it, the benefits to your organisation, and how your data stays private and secure.
1. Exposure and Accumulation Analysis
Swiss Re's CatNet is an online natural-hazard atlas that combines hazard, loss and exposure data with maps and satellite imagery. It assesses exposure at any location and accumulation across entire portfolios, and analyses near-real-time event footprints for earthquakes, tropical cyclones, windstorms and floods [1]. The same approach applies to any insurer's book: geocode every insured location, overlay hazard layers, and measure how much sum insured sits in each hazard zone.
Business problem
Many insurers hold policy addresses as free text, so they cannot say how much sum insured sits in one flood plain or cyclone track. With catastrophe losses rising [1], this blind spot leads to unplanned concentrations, surprise losses after a single event, and reinsurance bought without a clear view of the book. Underwriters also price new proposals without a consistent measure of location hazard.
Our solution
- Geocoding of the policy portfolio, with address cleaning and location quality flags.
- Overlay of flood, cyclone, earthquake, heat and other hazard layers to attach hazard attributes to every insured location.
- Accumulation dashboards showing sum insured by hazard zone, region, peril and product on WebGIS and Heatmap views.
- Location hazard scoring for new proposals, so underwriting can see the risk of a site before acceptance.
Benefits
- Sum insured by hazard zone measured, not estimated.
- Early warning of concentrations before they become a single-event loss.
- Better-informed reinsurance and capacity decisions.
- Underwriting prices that reflect the hazard at the insured location.
- Industry example: Swiss Re's CatNet assesses accumulation across entire portfolios using hazard, loss and exposure data [1].
Privacy & data security
- Policy addresses linked to policyholder names are personal data under the DPDP Act [2].
- Accumulation analysis works on location and sum insured; names and other identifiers can be removed or pseudonymised before analysis.
- Risk scoring is based on location and hazard only, never on the personal characteristics of policyholders.
- Data is encrypted in transit (TLS 1.2 or higher) and at rest (AES-256), with role-based access and audit logs.
2. Crop Insurance in India (PMFBY)
- YES-TECH. From Kharif 2023, remote-sensing-derived yields receive a mandatory 30% weightage alongside crop-cutting experiments for paddy and wheat. In Kharif 2023 all implementing states calculated and paid claims using YES-TECH, and no dispute was reported by any stakeholder [3].
- CCE-Agri App. States must capture crop-cutting experiments on smartphones and upload them to the National Crop Insurance Portal, and use satellite and drone remote sensing for area estimation, yield disputes, CCE planning and loss assessment [4]. In Kharif 2019, satellite-based smart sampling chose CCE locations in 96 districts across 9 states [5].
- Proof of insurable interest. A NITI Aayog task force recommended geotagged, time-stamped photographs of land as proof of insurable interest, and digitised geo-referenced land records to reduce moral hazard [6].
Business problem
Crop insurance is now technology-led: satellite yields carry a fixed 30% weight under YES-TECH and CCE data must be captured digitally [3][4]. Insurers face disputes over yield estimates, delays in claim calculation, and the cost of verifying insured area and insurable interest across lakhs of small plots. Without reliable geospatial evidence, claims are slow and contested.
Our solution
- NDVI and crop-condition time series and crop-area mapping for the insured area from satellite imagery.
- CCE planning support, including selection of sample locations based on crop condition.
- Digital CCE and survey forms in the My GLOBEIR app, with geotags, time stamps and photos, working offline in the field.
- Plot-level evidence of insurable interest using geotagged photographs and geo-referenced land records where available [6], displayed with the Digital Micro Mapping approach.
Benefits
- Objective, consistent yield and area evidence that supports YES-TECH calculations.
- Fewer yield disputes. Industry example: in Kharif 2023, all implementing states paid claims using YES-TECH and no dispute was reported by any stakeholder [3].
- Lower cost of field verification through better-targeted CCEs [5].
- Tamper-evident field data with location and time stamps.
Privacy & data security
- Farmer data includes names, land-parcel locations, bank details and geotagged photos of fields, all personal data under the DPDP Act [2].
- Crop-condition and yield analysis runs at plot or area level and does not need farmer identity; identifiers are linked only where a claim requires it.
- Field surveyor location is captured for work purposes, with opt-in tracking and a persistent notification.
- Data is shared only for the agreed purpose and is never sold or used for other clients.
3. Parametric Insurance
Parametric cover pays automatically when a measured index (wind speed, rainfall, vegetation, temperature) crosses a threshold in a defined area, so geography and data define the product.
- Mexico coral reef: a wind-speed-triggered policy paid USD 850,000 after Hurricane Delta in 2020 for reef restoration [7].
- Kenya Livestock Insurance Program: based on satellite vegetation monitoring, it paid USD 7 million to 18,000 herding households during the 2017 drought [8].
- Nagaland, India: the first Indian state to insure its entire geography against heavy rainfall. Its first claim, for Monsoon 2024, of ₹1,06,50,000 was settled in March 2025 [9][10].
- Extreme-heat income cover (2023): a parametric product designed with SEWA to protect 21,000 women workers, paying directly into bank accounts when temperatures pass a set threshold [11].
Business problem
A parametric product is only as good as its trigger. If the index or the trigger area does not match real losses on the ground (basis risk), policyholders lose trust and the product fails. Designing triggers needs long historical records of rainfall, wind, vegetation or temperature, careful choice of areas, and clear maps that regulators, reinsurers and customers can understand.
Our solution
- Historical index analysis of rainfall, wind, vegetation and temperature for the target region.
- Trigger-area mapping, with boundaries set by administrative units, grids or hazard zones.
- Back-testing of candidate triggers against past events to show how often and where they would have paid.
- Monitoring maps during the cover period, published on WebGIS for transparent tracking of the index.
Benefits
- Triggers grounded in data, with basis risk measured before launch.
- Faster, automatic payouts. Industry examples: Nagaland's state-wide rainfall cover settled its first claim [9][10], and the Kenya programme paid 18,000 households after the 2017 drought [8].
- Clear maps that help explain the product to regulators, reinsurers and customers.
- A reusable index library for new parametric products.
Privacy & data security
- Trigger design and index monitoring use environmental and area data, not personal data.
- Where payouts go to individuals, as in income cover [11], beneficiary records are kept separate from the index analysis and protected by role-based access.
- Area-level analysis keeps personal identifiers out of the product design workflow.
4. Claims Verification
After an event, satellite and drone imagery show the extent of flooding, crop damage or structural impact, and geotagged surveyor visits confirm individual claims. Imagery-based triage helps decide which claims need a physical visit and which can be fast-tracked. Flood maps from radar satellites can be produced even under monsoon cloud (see Environment).
Business problem
After a major event, claims arrive in large numbers at once. Sending a surveyor to every site is slow and costly, and delays hurt customers and the insurer's reputation. At the same time, claims without location and time evidence are easier to stage or inflate, which raises fraud losses.
Our solution
- Rapid flood and damage extent mapping from satellite and drone imagery, including radar imagery under cloud.
- Claims triage by location: claims inside mapped damage areas flagged for fast-tracking, claims outside flagged for review.
- Geotagged, time-stamped surveyor inspections through the My GLOBEIR app, with supervisor oversight through Live Tracking.
- Pre-agreed event-response workflows so mapping starts as soon as an event occurs.
Benefits
- Faster settlement for genuine claims.
- Fewer unnecessary physical visits and lower claims-handling cost.
- Fewer disputes, because decisions rest on shared map evidence.
- Stronger fraud control through location and time evidence.
Privacy & data security
- Claims files combine policyholder identity, property location, photos of homes and damage, and surveyor movement data.
- Access is restricted by role, with audit logs of who viewed or changed each claim.
- Surveyor tracking is optional and opt-in with a persistent notification, and used for work purposes only.
- Claims triage uses the location of the claim against the mapped hazard footprint, never the personal characteristics of the claimant.