ESWhy do decision-makers underinsure their logistics risks even when insurance is accessible?
*Article presented in collaboration with the Latin American Association of Maritime Subscribers (ALSUM).
Latin America continues to exhibit significantly low levels of insurance penetration (Fundación MAPFRE, 2024), a trend that is also reflected in marine cargo and transportation insurance. This article explores how behavioral factors interact with the characteristics of the regional insurance market and identifies concrete opportunities that go beyond traditional explanations based on structural variables such as cost, regulation, or access.
The conventional explanation attributes this protection gap to factors such as premium costs, limited product availability, lack of understanding of coverage, business informality, or low levels of financial literacy. However, these factors are insufficient to explain why decision-makers often choose not to insure their goods even when insurance products are accessible and cost-effective.
This behavior highlights that business decisions do not always follow a fully rational model—such as that of homo economicus, who maximizes utility based on all available information. This is where behavioral science complements traditional explanations by incorporating how people perceive, interpret, and respond to risk. Evidence shows that the relationship between price and risk alone is often insufficient to trigger the purchase of an insurance policy.
So, what aspects of human psychology help explain the barriers to insurance adoption? Below, we explore some of the cognitive shortcuts that may limit optimal decision-making.
Key Cognitive Biases Limiting Marine and Cargo Insurance Decisions
Availability Heuristic.
In 1973, two of the founding figures of behavioral economics, Amos Tversky and Daniel Kahneman, demonstrated that people estimate the probability of an event based on how easily they can recall similar examples. For instance, a logistics manager in Bogotá who has never experienced an intermodal cargo theft or a maritime loss is likely to dramatically underestimate the probability of such events, even when regional claims statistics indicate elevated risk levels. Records from the International Maritime Bureau (ICC-IMB, 2023) show that piracy and theft incidents in ports and anchorages across South America—including Callao (Peru), Macapá (Brazil), Cartagena, and Puerto Bolívar (Colombia)—remain tangible risks. Yet potential policyholders often underestimate these probabilities because they lack direct experience or cannot readily recall a recent case.
Optimism Bias.
Optimism bias refers to the tendency to overestimate the likelihood of experiencing positive outcomes while underestimating the probability of adverse events (Weinstein, 1980; Sharot, 2011). In Latin American business environments, where informality and reactive risk management practices are common, this bias acts as a significant barrier to insurance adoption. Decision-makers often believe that losses, theft, accidents, or disruptions are more likely to happen to others than to their own organizations. As a result, insurance is frequently viewed as a precaution that can be postponed rather than as an essential component of risk management.
Loss Aversion
One of the most robust findings in behavioral economics is loss aversion, which suggests that people experience the pain of a loss approximately two to two and a half times more intensely than the pleasure associated with an equivalent gain (Kahneman & Tversky, 1979). Paradoxically, this principle predicts both the overestimation of risk in some contexts—which should encourage insurance adoption—and resistance to paying premiums in others. For the insurance industry, this bias is particularly relevant because premium payments are perceived as an immediate and tangible loss. By contrast, insurance coverage represents an uncertain future benefit that is often difficult to visualize concretely. Consequently, decision-makers perceive the cost of the premium as a more significant loss than would be justified under a rational expected-utility analysis. Even when insurance is actuarially advantageous, this bias can lead organizations to delay or avoid purchasing coverage altogether. In the marine and transportation sectors, where premiums for high-value cargo often represent only a small fraction of the insured value, the perception of premiums as a “cost with no visible return” remains a substantial behavioral barrier.
Mental Accounting.
Thaler (1985) describes how people categorize financial resources into separate “mental accounts” and apply different valuation rules to each of them. In business settings, insurance budgets are frequently perceived as an “unproductive operating expense”, while investments in infrastructure, technology, or logistics capabilities are categorized as “strategic investments”. This categorization distorts cost-benefit evaluations and limits a company’s ability to objectively assess the value of insurance, regardless of its actual economic benefits.
Hyperbolic Discounting.
Hyperbolic discounting refers to the tendency to favor immediate rewards—even if they are smaller—over larger benefits that will materialize in the future. In the insurance context, this means that the immediate and tangible cost of a premium weighs more heavily than the potential benefits of coverage, which are contingent and realized only if a future loss occurs. As a result, even when insurance is highly cost-efficient over the long term, this bias reduces the likelihood that individuals or organizations will purchase coverage.
Closing the Protection Gap: Opportunities, Solutions, and Strategic Impact Through Behavioral Science
From a behavioral science perspective, diagnosis is not merely descriptive—it also provides practical intervention opportunities through decision architecture, the environment in which choices are made.
These approaches are already helping insurers overcome behavioral barriers such as those described above, while also improving product design, sales performance, claims management, ecosystem development, fraud reduction, and both customer and employee satisfaction (Becker et al., 2020).
Some examples include:
Simplification and Reframing of Risk Communication: reducing product complexity and communicating risk in terms of potential losses can significantly improve decision-making. The use of clear language, compelling narratives, and concrete visual comparisons helps customers better understand the value of insurance and the consequences of remaining uninsured (BIT, 2025).
Leveraging Defaults: default options are a powerful behavioral tool because people tend to stick with pre-selected choices during decision-making processes (Dinner et al., 2011). In logistics operations, this principle could be applied by making insurance coverage the default option within transportation or shipping processes, while still allowing customers to opt out if they choose.
Behavioral Timing: offering insurance at moments when risk perception is naturally heightened—or at other strategically relevant moments—can increase adoption rates (BIT, 2025). Examples include the beginning of a commercial relationship, immediately after a loss event within the industry (whether experienced directly or indirectly), or during the financing process for an international trade operation.
Closing the insurance protection gap in Latin America requires an agenda that combines structural reforms with behavioral interventions. Neither approach is sufficient on its own. The most effective strategy lies in integrating both.
Incorporating behavioral science not only improves commercial indicators such as product adoption and customer experience but also contributes to a more resilient and better-protected market by reducing underinsurance and enabling better decision-making among stakeholders.
Numerous insurers have already begun incorporating behavioral techniques across different stages of their value chain and have achieved significant results. One example involves a multi-line insurer in Germany that discovered that only a small percentage of customers filing auto insurance claims chose to use the company’s preferred repair network, despite it being a more convenient and cost-effective option. Within just four weeks, the insurer redesigned the language and conversations used by its claims representatives, incorporating behavioral science principles to better communicate the value of the offering. The results were compelling: acceptance rates exceeded 30%, and among third parties—traditionally a particularly difficult audience to influence—adoption increased from approximately 10% to 30%. The company subsequently expanded these behavioral interventions throughout its claims operation, ultimately reducing its loss ratio by 2% (Becker et al., 2020).
Organizations that fully recognize the potential of behavioral science can take an additional step by institutionalizing these capabilities through specialized teams or business units. This approach helps ensure that behavioral insights are embedded across the organization and systematically applied to decision-making processes, customer interactions, and strategic initiatives (Güntner et al., 2019).
Closing the maritime and transportation insurance gap in Latin America requires more than improving access, reducing costs, or expanding product availability. It also requires understanding how people make decisions under uncertainty.
Behavioral biases such as the availability heuristic, optimism bias, loss aversion, mental accounting, and hyperbolic discounting can systematically influence insurance decisions, even when coverage is economically rational and readily accessible.
By combining structural reforms with behavioral interventions, insurers can improve product adoption, strengthen customer relationships, and contribute to a more resilient and better-protected regional economy.
Behavioral science offers a practical framework for achieving these goals—one that enables organizations not only to understand decision-making but also to design environments that support better choices.
Are you interested in exploring how these concepts can be applied to the insurance market in Latin America? We would love to hear your thoughts and experiences.
References
Becker, G., Dreller, A., Güntner, A., & Lorenz, J.-T. (2020, September 21). Behavioral science in insurance—Nudges improve decision making. McKinsey & Company. Retrieved from https://www.mckinsey.com/industries/financial-services/our-insights/insurance-blog/behavioral-science-in-insurance-nudges-improve-decision-making
Behavioural Insights Team (BIT). (2025). EAST: Four simple ways to apply behavioural insights (Revised and updated edition).
Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011). Partitioning default effects: Why people choose not to choose. Journal of Experimental Psychology: Applied, 17(4), 332–341.
Fundación MAPFRE. (2024). El mercado asegurador latinoamericano en 2023 [The Latin American insurance market in 2023]. Retrieved from https://documentacion.fundacionmapfre.org/documentacion/publico/es/media/group/1125847.do
Güntner, A., Lucks, K., & Sperling-Magro, J. (2019, January 24). Lessons from the front line of corporate nudging. McKinsey Quarterly. Retrieved from https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/lessons-from-the-front-line-of-corporate-nudging
International Chamber of Commerce – International Maritime Bureau (ICC-IMB). (2023). Piracy and Armed Robbery Against Ships: Report for the Period 1 January–31 December 2023. Retrieved from https://www.icc-ccs.org/reports/2023_Annual_IMB_Piracy_and_Armed_Robbery_Report_live.pdf
Kahneman, D., & Tversky, A. (1977). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263–291.
Sharot, T. (2011). The optimism bias. Current Biology, 21(23), R941–R945.
Thaler, R. H. (1985). Mental accounting and consumer choice. Marketing Science, 4(3), 199–214.
Tversky, A., & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology, 5(2), 207–232.
Weinstein, N. D. (1980). Unrealistic optimism about future life events. Journal of Personality and Social Psychology, 39(5), 806–820.
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