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📐 '''Risk aggregation''' is the process of combining individual risk exposures across an insurer's portfolio to understand the total potential loss that could arise from a single event, correlated set of events, or common underlying factor. In insurance, isolated policies may each appear manageable on their own, yet when a [[Definition:Catastrophe | catastrophe]] like a hurricane strikes a region, thousands of those seemingly independent [[Definition:Exposure | exposures]] can trigger [[Definition:Claims | claims]] simultaneously. Risk aggregation provides the analytical framework that reveals these hidden concentrations before they become solvency-threatening surprises.

🔍 Carriers aggregate risk using a combination of [[Definition:Catastrophe model | catastrophe models]], [[Definition:Geographic information system (GIS) | geospatial analytics]], and internal [[Definition:Actuarial analysis | actuarial analysis]]. The process typically involves geocoding insured properties, mapping [[Definition:Policy limit | policy limits]] and [[Definition:Deductible | deductibles]] against modeled loss scenarios, and summing potential losses at various return periods. For a multi-line insurer, aggregation extends beyond natural catastrophe exposure to encompass [[Definition:Cyber risk | cyber risk]], [[Definition:Casualty insurance | casualty]] clash scenarios, and [[Definition:Terrorism risk | terrorism]] accumulations. [[Definition:Reinsurance | Reinsurance]] purchasing decisions depend heavily on aggregation output: without a clear picture of probable maximum loss, an insurer cannot structure an efficient [[Definition:Reinsurance program | reinsurance program]] or negotiate appropriate terms with [[Definition:Reinsurer | reinsurers]].

⚠️ Regulatory frameworks such as [[Definition:Solvency II | Solvency II]] and the [[Definition:National Association of Insurance Commissioners (NAIC) | NAIC's]] risk-based capital standards require insurers to demonstrate robust aggregation capabilities and to hold capital commensurate with their aggregate exposures. The consequences of weak aggregation discipline have been demonstrated repeatedly — notably when insurers discovered after major events that their actual losses far exceeded modeled expectations due to unrecognized correlations or data gaps. [[Definition:Insurtech | Insurtech]] firms are advancing aggregation technology by integrating real-time data feeds — satellite imagery, IoT sensor data, and [[Definition:Artificial intelligence (AI) | AI]]-driven portfolio scanning — that allow underwriters to monitor accumulations dynamically rather than relying on quarterly static reports.

'''Related concepts'''
{{Div col|colwidth=20em}}
* [[Definition:Catastrophe model]]
* [[Definition:Probable maximum loss (PML)]]
* [[Definition:Exposure management]]
* [[Definition:Reinsurance program]]
* [[Definition:Solvency II]]
* [[Definition:Concentration risk]]
{{Div col end}}

Definition:Risk aggregation - Revision history

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