The UrClimate Suite
Comprehensive SaaS products for climate risk assessment, from screening
to financial quantification.
Physical Risk Scoring
UrClimate Score
Instant property-level climate risk scores for underwriting and portfolio screening. Powered by advanced meteorological models and machine learning.
- Multi-hazard risk scoring (8+ perils)
- Property-level granularity
- Real-time API access
- TCFD-aligned reporting
Custom Analytics Platform
UrClimate Tailor
Bespoke climate risk analytics tailored to your specific portfolio, risk appetite, and reporting requirements.
- Customizable risk models
- Portfolio aggregation
- Scenario analysis (RCP/SSP)
- White-label dashboards
Financial Impact Quantification
UrClimate Next
Transform physical risk data into financial metrics. Calculate AAL, stress test portfolios, and meet IFRS S2 disclosure requirements.
- Annual Average Loss (AAL)
- Expected Annual Loss (EAL)
- Financial stress testing
- IFRS S2 / TSRS compliance
Municipal Climate Platform
UrClimate Kent
GHG inventory, physical climate risks and finance readiness — the climate platform built for municipalities.
- Scope 1–2–3 GHG inventory
- 9 physical hazard maps
- GPC & CDP-ready reporting
- Access to Finance module
How it works
We define the problem and the right scale
We clarify the asset or portfolio objective, geographic scope, hazard set (e.g., heatwaves, storm/wind, flooding, wildfire), and performance criteria. At this stage, we determine which decision will be supported (design, investment, insurance, or operations) and define the appropriate spatial/temporal resolution and output format. Step label (desc.): Objective + scope
Step 1
We build a multi-scale modelling framework
We combine climate and meteorological data with topography, land use, urban geometry, and project-specific site inputs. By selecting the appropriate physical approach (e.g., WRF, CFD, hydrologic–hydraulic modelling), we establish a consistent solution chain from macro to micro scales and apply quality control, calibration, and technical verification to ensure reliability. Step label (desc.): Model + validation
Step 2
We translate results into decision outputs
We turn results into decision-ready deliverables: risk indicators, scenario comparisons, sensitivity/exposure insights, and improvement/adaptation options. Where required, we link these outputs to financial impact metrics and deliver them in the format best suited to the use case—report, map, interactive dashboard, or API. Step label (desc.): Report / API / Dashboard
Step 3
LinkedIn Highlights
Selected posts by Güven Fidan and Alkazar; follow both profiles for the full feed.
A number that is not on the table does not shape the decision either.
A note from the closing panel of a sustainable finance and investment forum: until the present value of future climate damage is put in front of every decision, investment decisions remain incomplete.
AlkazarCompany pageA factory lives for thirty years. The climate it was designed for does not.
A plant's fate is decided at the drawing board and in the choice of site, so how flood, drought, heat, storm and wildfire risk will evolve over its lifetime belongs in that decision.
What happened to the world this summer, and why does it affect everyone's pocket?
His Turkish-language newsletter looks at the present-day effects of climate change and our growing vulnerability in paying energy bills and accessing healthy food.
AlkazarCompany pageOn the hottest day of the year, the fate of a data centre is often decided on its roof.
When exhaust air finds its way back into the intakes, redundancy offers little protection. External CFD shows this failure mode at the design stage, long before construction.
Climate-driven risks need to be assessed separately for every asset type.
Global climate scenario data works for portfolio screening but cannot represent an individual site; calibrated site data is what reveals a facility's real financial exposure.
AlkazarCompany pageAct of nature, or design? Every solar PV snow damage claim comes down to that question.
For claims teams: independent cause attribution, a foreseeability backtest and damage pattern analysis, with a stated level of confidence for every finding.