The expansion of foreign trade in Latin America has significantly increased cargo values concentrated in major ports, raising a critical underwriting question: how much insured value is simultaneously exposed within these infrastructures under normal and disrupted conditions?
Ports are vulnerable to operational interruptions such as labour strikes, access constraints, congestion, and system failures, all of which extend cargo dwell time and amplify accumulation risk. Traditional approaches based on aerial imagery or 3D models allow visualisation of physical volumes but fail to quantify the economic value of stored goods. For marine insurers and reinsurers, exposure depends on monetary value, not physical space.
A more robust approach applies a fundamental logistics principle formalised in Little’s Law: inventory equals flow multiplied by dwell time. Based on this concept, a structured three-stage methodology is proposed.
Methodological framework
- Identification of peak flow month
For each port, the month with the highest combined import and export value during the year is selected, representing maximum operational pressure. Data may be sourced from customs authorities or port administrations.
- Determination of average dwell time
Average cargo permanence is obtained from port authorities, customs agencies, or international benchmarks such as the World Bank’s Logistics Performance Index (LPI).
- Estimation of simultaneous inventory
The exposed value is calculated by multiplying peak flow by dwell time, incorporating disruption adjustments:
Where:
Fi = Monthly value handled by cargo type i
Ti = Average dwell time by cargo type i
Tinterruption,j = Additional disruption time by risk type j
Total Inventory = Estimated simultaneous exposed value
This structure allows scenario modelling by cargo type and disruption category.
Empirical application
Applying this methodology to Colombia using proprietary calculations indicates that, under normal conditions, the two main ports concentrate between USD 580–660 million in exposed cargo, excluding hydrocarbons and coal. Under moderate congestion, exposure increases by more than 12.5% per additional day. A 10-day disruption may elevate accumulations to approximately 2.25 times the baseline exposure.
Note: Import and export flows were derived from DIAN foreign trade statistical databases (2026), processed in Microsoft Excel using Power Query, consolidating annual FOB and CIF values and excluding oil and coal.
Advantages and limitations
The methodology is theory-based, transparent, replicable, and comparable across ports. It relies primarily on publicly available data and supports scenario development for probable maximum loss (PML) modelling. It enhances dialogue between insurers, reinsurers, and supervisors.
However, it does not capture extreme short-term peaks or intramonth volatility. Therefore, it should be interpreted as a structured estimation rather than an absolute measurement.
Strategic implications
By interpreting cargo flows as inventories, dispersed trade statistics become actionable underwriting intelligence. In a context of increasing operational and climate volatility, systematic measurement of port accumulations is essential for strengthening marine insurance sustainability and reinsurance placement strategies in Latin America.
