Asset Risk & Insurance Intelligence v26

Real/referenceSaudi regional structure13-region reporting frame.

ReferenceKSA map outlineInline vector outline approximates the actual country shape for visualization; not official GIS.

SYNTHETICAssets, values, losses, premiumsAll asset records and insurance outputs are synthetic and stress-tested for demo use.

Assets shown

Filtered portfolio

Replacement value

Synthetic USDm

Expected annual loss

Scenario-adjusted

Expected recovery

Coverage-adjusted

Estimated premium

Illustrative premium

Residual risk

Risk retained

Positioning: This is a decision-support prototype. It uses reference geography for framing and synthetic, stress-tested financial data for analytics.

Core Metric Definitions

Key formulas used across the dashboard. These are synthetic demo formulas and should be recalibrated with actual client, broker, and actuarial inputs.

Expected Annual Loss

Gross EAL = Replacement Value × Annual Probability × Damage Ratio
EAL = Gross EAL × (1 − Mitigation Effectiveness)

Represents the expected annualized loss before and after assumed mitigation/control effectiveness.

Source: synthetic actuarial-style assumption

Expected Recovery

Expected Recovery = EAL × Coverage Ratio

Estimated portion of expected annual loss transferred to insurance or risk financing.

Source: synthetic insurance assumption

Residual Risk

Residual Risk = EAL − Expected Recovery

Estimated expected loss retained after insurance recovery or other financing mechanisms.

Source: synthetic residual-risk calculation

Executive storyline

The tool supports a practical risk financing conversation.

ClassifySegment assets by region, category, hazard, and risk band.

PrioritizeRank assets by risk, criticality, and dependency.

InsureCompare premium, recovery, and residual risk.

SimulateStress-test scenarios and retained exposure.

Risk Band Distribution

Gross-to-Residual Risk Bridge

Top Regional Residual Risk

KSA Map

Offline SVG map using Natural Earth country boundary coordinates. It does not rely on external tiles or offline SVG. Use the zoom controls to inspect Saudi Arabia and neighbouring countries.

Real/referenceCountry boundariesSaudi Arabia and neighbouring country outlines use Natural Earth-style country boundary coordinates from the world.geo.json dataset.

Source: Natural Earth-derived world.geo.json country boundaries.

ReferenceRegion labelsSaudi region labels are approximate anchor locations for navigation only, not official region polygons.

Source: reference coordinates embedded in prototype.

SYNTHETICAsset pointsAsset locations, values, losses, premiums, residual risk, and risk bands are synthetic and calibrated for demonstration. Hover over a marker for details.

Source: synthetic asset register.

Map controls: use + / − to zoom, then click-drag or touch-drag the map to pan left, right, up, or down.

Critical High Medium Lower

Scenario Lab

Choose a stress event, tune assumptions, then run the simulation. Every parameter below includes a description and data-source status.

Scenario preset

Selects which hazards receive scenario uplift when the simulation is run.

Source: synthetic scenario design

Locks in the selected scenario preset and applies scenario parameters to the filtered portfolio.

Source: dashboard interaction

Event severity1.25x

Multiplier applied to loss for assets affected by the selected stress event.

Source: synthetic stress assumption

Assets affected55%

Share of hazard-relevant assets assumed to be impacted in the simulated event.

Source: synthetic exposure assumption

Claims inflation8%

Additional uplift to claims cost due to repair inflation, supply-chain pressure, or surge demand.

Source: synthetic claims assumption

Mitigation degradation10%

Assumes controls perform worse than expected during a severe event.

Source: synthetic operational resilience assumption

Recovery capacity shock0%

Adjusts insurance recovery ratio for affected assets, reflecting limits, exclusions, or improved coverage.

Source: synthetic insurance assumption

Premium market hardening15%

Additional premium loading after a stress event or market hardening cycle.

Source: synthetic pricing assumption

Scenario Calculation Methodology

How the Scenario Lab adjusts the baseline synthetic portfolio after clicking Run simulation.

Scenario EAL

Scenario EAL = Base EAL × Manual Severity × Scenario Loss Factor

The scenario loss factor applies only to assets affected by the selected scenario preset and affected-asset share.

Source: synthetic scenario stress logic

Scenario Loss Factor

Scenario Loss Factor = Event Severity × (1 + Mitigation Degradation) × (1 + Claims Inflation)

Used for affected assets to represent worse event intensity, reduced control effectiveness, and higher claim costs.

Source: synthetic stress assumption

Scenario Premium

Scenario Premium = Base Premium × Recovery Change × (1 + Premium Market Hardening)

Applied to affected assets to show how premiums may change after a severe event or market hardening cycle.

Source: synthetic pricing assumption

Simulation Waterfall

Base EAL to simulated residual risk.

Financing Stack

How the simulated loss is absorbed.

Impact by Hazard

Impact by Region

Sensitivity Drivers

Top Assets Driving Scenario Loss

Priority Score Methodology

The priority score is a synthetic ranking score used to compare assets. It is not an actuarial loss estimate; it is designed to help triage which assets require deeper review.

Priority Score

Priority Score = Criticality × Likelihood × Impact × Vulnerability × Interdependency Factor × Exposure Multiplier

Higher scores indicate assets that are more critical, more exposed, harder to replace, or more likely to create cascading operational impacts.

Source: synthetic prioritization methodology

Input scales

Criticality, Likelihood, Impact, Vulnerability = 1 to 5
Interdependency Factor ≈ 0.85 to 1.75
Exposure Multiplier ≥ 1.00

The 1–5 scales are synthetic scoring assumptions. In a real implementation these would be replaced by client-approved scoring criteria.

Source: synthetic scoring assumptions

Risk banding

Critical ≥ 290
High ≥ 160
Medium ≥ 75
Lower < 75

Risk bands are threshold-based categories for dashboard readability, not regulatory classifications.

Source: synthetic threshold design

Top Priority Assets

Residual Risk by Hazard

Insurance Metric Definitions

Definitions for the insurance analytics shown below.

Estimated Premium

Estimated Premium = Expected Recovery × (1 + Insurance Loading Factor)

The loading factor is a synthetic assumption varying by insurance option, intended to represent expense, margin, volatility, and market hardening.

Source: synthetic pricing assumption

Premium Efficiency

Premium Efficiency = Expected Recovery ÷ Estimated Premium

A simple ratio showing expected recovery per $1 of estimated premium. Higher is more efficient.

Source: calculated from synthetic recovery and premium

Protection Gap

Protection Gap = Residual Risk

In this prototype, the protection gap is shown as the retained residual expected loss after expected insurance recovery.

Source: synthetic residual-risk calculation

Insurance Portfolio Mix

Premium, recovery, and residual risk by insurance option.

Insurance Efficiency

Expected recovery per $1 of premium.

Coverage Gap by Insurance Option

Premium vs Recovery Scatter

Regional Residual Risk Ranking

Regional Expected Recovery

Real / Reference Data Sources

These items are used only for geographic or structural context. They are not the asset, loss, or pricing dataset.

REFERENCE Country boundaries Saudi Arabia and neighbouring country outlines use Natural Earth-derived country boundary coordinates from the world.geo.json dataset. These are suitable for visual context, not official cadastral or legal boundaries.

Reference Saudi region labels Region names are placed using approximate anchor coordinates so users can navigate the map. They are labels only and do not represent official region polygons.

Reference Map display The map is rendered offline as SVG inside the HTML, so it does not depend on external map tiles, web services, or Leaflet sizing.

Synthetic Data and Assumptions

These items are illustrative and should be replaced with client-approved data in production.

SYNTHETIC Asset register Asset names, asset categories, locations, replacement values, vulnerability scores, and risk bands are synthetic and calibrated for demonstration at KSA country scale.

SYNTHETIC Risk and insurance calculations Expected annual loss, expected recovery, residual risk, estimated premium, premium efficiency, and protection gap are calculated using synthetic methodology assumptions.

SYNTHETIC Scenario Lab assumptions Event severity, affected asset share, claims inflation, mitigation degradation, recovery capacity shock, and premium market hardening are scenario assumptions for demonstration.

Asset Register

Search, sort, click an asset row for drill-down, or export filtered data.