Identifying insurance literacy knowledge gaps across the insurance product lifecycle: a qualitative thematic analysis

Financial well-being is increasingly shaped by consumers’ ability to navigate complex financial decisions. As financial products become more sophisticated, financial literacy has emerged as a key determinant of financial well-being, influencing how individuals are equipped with essential skills for resource management, risk evaluation and long-term financial planning (Finke and Huston, 2014). Commonly defined as the ability to understand and apply financial knowledge to make informed decisions (Lusardi and Mitchell, 2014), financial literacy constitutes a fundamental component of human capital.

The effects of financial literacy extend beyond personal finance, shaping economic behaviour, resilience and participation in financial markets. From a societal perspective, financial literacy promotes market participation and economic resilience. Financially literate consumers are more likely to engage in financial planning and participate in financial markets, contributing to market efficiency and reducing systemic vulnerabilities (Oehler et al., 2024; Bongini et al., 2023). Enhancing financial literacy therefore aligns closely with regulatory and policy objectives aimed at inclusive growth and financial stability. Persistent gaps in financial knowledge highlight the need for targeted education and policy interventions. Advancing financial literacy is thus not only an individual benefit but a societal necessity, with the potential to improve overall well-being, reduce inequality and strengthen financial systems (Lusardi, 2015).

Within this broader financial literacy framework, insurance literacy demands particular attention. Insurance markets create conditions in which literacy gaps easily emerge, as insurance products are often complex, involve long-term commitments and require consumers to evaluate abstract risks and contractual conditions. Previous research has argued that consumers frequently lack sufficient understanding of insurance products, leading to suboptimal purchasing decisions, unmet expectations and consumer disputes (Sun and Yuan, 2024).

The regulatory environment is crucial in shaping how insurance products are designed, distributed and understood. At the EU level, regulation seeks to enhance consumer protection through common standards for conduct, transparency and product governance, including the insurance distribution directive (IDD), which establishes conduct of business requirements, and product oversight and governance (POG) rules that guide product design and target market identification, as well as standardised disclosure tools such as insurance product information documents (IPIDs). These instruments rest on the implicit assumption that consumers can meaningfully engage with, interpret and act upon the information provided. As a result, market outcomes depend not only on regulatory compliance on the supply side but also on consumers’ ability to understand information and make informed decisions. When this premise fails, mismatches between regulatory intent and consumer outcomes may emerge, often becoming visible in consumer complaints and dispute resolution processes.

This paper examines insurance literacy gaps through alternative dispute resolution cases, offering empirical insights into actual consumer misunderstandings and their consequences. The primary research question guiding this paper is: What types of insurance literacy gaps can be identified in consumer disputes across the insurance product lifecycle, and how do these gaps manifest in consumer decision-making? To address this question, Section 2 reviews the theoretical foundations of financial and insurance literacy. Section 3 outlines the research methodology, Section 4 presents the empirical findings along with a discussion, while Section 5 concludes with key contributions, practical implications, limitations and opportunities for future research.

Financial literacy is regarded as an essential component of human capital, enabling individuals to navigate increasingly complex financial environments and make informed decisions. Finke and Huston (2014) conceptualised financial literacy as the knowledge and skills required for effective personal financial management, including mathematical competence, familiarity with financial products and the ability to apply this knowledge in practice. This perspective emphasises that financial literacy extends beyond information acquisition to include cognitive processing and reasoning. Similarly, Remund (2010) defined financial literacy as a combination of knowledge, skills, confidence and motivation, highlighting the importance of psychological readiness and behavioural capacity alongside cognitive understanding.

The determinants of financial literacy are multidimensional, encompassing individual characteristics such as education, attitudes, skills and confidence alongside structural factors including regulatory, normative and cultural-cognitive frameworks (Santini et al., 2019; Okello Candiya Bongomin and Munene, 2020).

Beyond individual knowledge, financial literacy has broader implications for engagement with financial systems and personal well-being. Higher literacy is associated with greater access and use of financial services (Song et al., 2024). In spite of extensive financial education initiatives, substantial gaps remain, especially in more advanced areas such as risk diversification and financial market functioning (van Rooij et al., 2011), reinforcing concerns about uneven literacy levels across populations (Goyal and Kumar, 2021). In this sense, financial literacy functions not only as an individual capability but also plays a role within the broader context that shapes the practical effectiveness of consumer protection measures embedded in financial regulation.

Lin et al. (2019) argued that general financial knowledge is insufficient for well-informed insurance decisions, highlighting insurance literacy as a distinct subdomain of financial literacy. Insurance literacy requires specialised expertise, including abstract reasoning, probabilistic thinking and the ability to assess long-term uncertainty. It enables individuals to recognise insurable risks, understand insurance products and contractual arrangements and make informed decisions under conditions of uncertainty.

This paper adopts the insurance literacy framework proposed by Sanjeewa and Hongbing (2019) as its conceptual foundation (Table 1). The framework specifies six distinct knowledge dimensions as illustrated above. In this study, these dimensions are organised into four broader knowledge areas to reflect how insurance literacy manifests in practice. As will be demonstrated in Section 4 (Results), dispute cases indicate that these dimensions are rarely considered individually. Rather, they are activated through a combination of risk exposure, scope of coverage, contractual obligations and information sources. The consolidation therefore serves a presentational and analytical purpose, improving coherence without altering the underlying conceptual structure of the original framework.

The analysis further adopts a lifecycle-based perspective aligned with the insurance product lifecycle outlined by the European Insurance and Occupational Pensions Authority (EIOPA, 2019). This perspective situates insurance literacy across all stages of the insurance relationship, from pre-contractual decision-making through product design, marketing and sales to policy management and claims handling. Viewing insurance literacy as a dynamic, lifecycle-spanning competence allows for a more nuanced understanding of how insurance literacy knowledge gaps may lead to recurring mismatches between consumer expectations and regulatory objectives.

Identifying and managing risks requires consumers to combine awareness of potential exposures with strategies for mitigation, reflecting their ability to recognise insurable risks and understand insurance as a tool for addressing harmful events. As Kunreuther et al. (2013) noted, these processes are cognitively inseparable. However, consumers struggle to determine which risks are genuinely relevant to their personal circumstances. Effective risk recognition depends not only on awareness of possible events but also on accurately assessing their significance. When perceived controllability is low or confidence in managing uncertainty is limited, risk evaluations become distorted, leading individuals to overlook substantial risks or focus disproportionately on unlikely events, reflecting risk perception biases, including probability misestimation (Buehler and Maas, 2018).

Cognitive biases further intensify these challenges. Overconfidence bias leads consumers to overestimate their understanding of both risks and insurance needs, increasing the likelihood of underinsurance, where insurance does not cover the full cost of a loss or expense (Driver et al., 2025). Similarly, systematic errors in probability assessment (such as underestimating the likelihood or impact of adverse events) contribute to insufficient coverage (Pitthan and De Witte, 2021). These behavioural tendencies are compounded by low insurance literacy and information asymmetry in risk assessment: access to insurance products does not guarantee comprehension or informed decision-making (Han and Jang, 2013). As a result, consumers may misjudge both their exposure to risk and the adequacy of available policies, reinforcing coverage gaps.

Low literacy affects not only early coverage decisions but also ongoing policy management. Consumers with limited understanding may perceive reviewing or updating coverage as unnecessary or overly complex, leading to outdated protection as circumstances change. In contrast, higher literacy is associated with more informed choices, such as selecting appropriate deductibles, balancing premiums with coverage needs and engaging in sound financial planning (Boes and Liu, 2024).

Consumers may hold unrealistic expectations about insurance compensation, mixing general financial literacy with insurance-specific knowledge. Even financially literate individuals may misunderstand coverage, particularly for complex products with conditional or limited terms (Lin et al., 2019). These misunderstandings shape expectations and can lead to dissatisfaction or disputes when outcomes diverge from assumptions. Misconceptions also extend to the purpose of insurance itself: individuals who perceive themselves as healthy may underestimate their need for coverage, failing to recognise insurance as a mechanism for risk transfer, reflecting mental models and misconceptions of risk transfer rather than a reflection of current health status (Browne and Zhou-Richter, 2014). In contrast, higher insurance literacy is associated with more proactive engagement, including greater use of health-care services, as consumers view insurance as a means of accessing and financing care rather than merely a safety net (Yagi et al., 2022).

Understanding is further complicated by the technical language and structural complexity of insurance contracts, highlighting bounded rationality and cognitive limitations. Difficult or specialised wording challenges comprehension (Van Boom et al., 2016), and while improved readability could enhance trust and confidence, clarity alone is insufficient. Standardised formats do not necessarily improve understanding of exclusions or limitations, indicating that conceptual transparency is more important than presentation alone (Taha et al., 2023; Dexe et al., 2021). This limitation is also reflected in the EU Retail Investment Strategy, which notes that consumers often face complexity and information overload, emphasising the need for clear and comprehensible information rather than simply more of it. It highlights that increasing information does not necessarily improve understanding and may instead make decision-making more difficult. Consistent with this, many consumers possess only a limited, surface-level understanding of insurance products and lack detailed knowledge of specific features, limitations or applicability (Kousky and Netusil, 2023), creating a gap between perceived and actual comprehension.

This complexity also undermines product comparability and informed choice. When key details are disguised by technical language or complex conditions, consumers struggle to weigh options or align coverage with their needs. As a result, decisions are often driven by marketing cues or brand familiarity rather than substantive analysis. Inability to distinguish between exclusions, deductibles and coverage can lead consumers to overestimate their level of protection and remain unaware of critical gaps. In addition, insurance product terminology is not necessarily standardised, and product labels may function as marketing descriptions rather than strictly comparable categories. These interpretive challenges not only affect product choice but also frame how consumers perceive their rights and responsibilities.

Understanding one’s rights plays a significant role in how consumers approach compensation and behave during the claims process (Armeanu et al., 2014). However, persistent information asymmetries between insurers and customers complicate this relationship, as consumers lack clarity about disclosure obligations, evidentiary requirements and the consequences of failing to meet them (de Jong, 2021). These misunderstandings can be perceived as structural rather than intentional, resulting in disputes driven by confusion over procedures rather than dishonesty. Consequently, ambiguities in claims processes can weaken consumer confidence and reflect procedural ambiguity and legal uncertainty.

Moreover, unclear communication and procedural requirements can diminish trust and increase perceptions of unfairness. Customer service quality is closely linked to satisfaction with complaint resolution and overall trust in insurers (Wendel et al., 2011), and poor communication may create the impression that information is being withheld or that decisions are opportunistic. Such ambiguities – relating to documentation, deadlines or evaluation criteria – intensify power imbalances and consumer frustration, particularly during periods of loss. Ultimately, the ability to exercise their rights and responsibilities effectively depends on access to clear and timely information, underscoring the role of trust and communication theory.

Finding, interpreting and applying relevant information remains a fundamental challenge in insurance literacy (Bardy, 2024). Many consumers struggle to access and evaluate information independently and therefore rely heavily on interpersonal trust, particularly trust in intermediaries, when making decisions, reflecting heuristics and trust-based decision-making (Luna-Cortés and Brady, 2025). While targeted and simplified communication can reduce cognitive demands and support decision-making by highlighting essential details (Bardy and Boes, 2024), this reliance on trusted sources may limit autonomous decision-making. Over time, however, insurance literacy tends to evolve. As consumers gain experience, they seem to shift away from informal advice from friends or family towards more formal and direct information channels (Colón-Morales et al., 2021), reflecting increasing independence in engagement and experiential learning.

Public communication, media and marketing play a significant role in shaping consumer awareness and expectations of insurance (Feng et al., 2024). Narratives that emphasise benefits while downplaying limitations can lead to inflated expectations, particularly when the primary goal is sales rather than providing balanced information, demonstrating narrative and persuasion effects. The interplay between trust in intermediaries and independent information-seeking is therefore crucial: consumers who rely heavily on intermediaries may misunderstand policies if their expectations do not align with the actual terms. Evidence from retail investment markets demonstrates that the way information is presented matters (Oehler et al., 2014). Consequently, insurance literacy depends on information that is clearly and thoughtfully designed, highlighting the importance of information design and choice architecture.

This paper examined consumer–insurer disputes to identify literacy gaps across the insurance product lifecycle and assessed how these gaps influenced decision-making. A qualitative approach was adopted to explore consumers’ knowledge and insurance event outcomes rather than to quantify the frequency of specific issues. Given this focus, the study aimed to generate insights rather than statistical generalisations.

Empirical data was sourced from recommended solutions issued by FINE, a financial sector organisation encompassing the Finnish Financial Ombudsman Bureau and three complaints boards covering insurance, banking and investment-related matters. Within the Finnish financial dispute resolution system, FINE plays an independent role by providing guidance and issuing recommendations to resolve disputes encountered by consumers, small and medium-sized enterprises and similar customer groups in financial services. Although FINE’s recommendations are formally non-binding, they carry substantial practical significance. Financial institutions in Finland generally comply with these recommendations, resulting in a high adherence rate (99.6% in 2025). As a result, FINE’s recommended solutions put forth a strong actual steering effect on industry practices and dispute resolution outcomes. This makes the data set a credible and representative source for analysing real consumer protection issues and market conduct in the Finnish financial sector.

The study relied exclusively on this secondary data set and involved no direct interaction with customers. Consequently, formal ethical review or informed consent was not required. Although underlying background documentation was not available for examination, each recommended solution included relevant facts, arguments from both parties, applicable policy wording and the rationale behind the solution. The data set covered recommended solutions issued between 2022 and 2024 and focused on widely used insurance products relevant to household financial security, including motor, home, property, liability, legal, health, accident and travel insurance. The data set consisted of disputes escalated to FINE, meaning that cases resolved at earlier advisory stages or not pursued further by consumers were excluded. In addition, no demographic information such as age, education or income was available. An initial set of 1,100 recommended solutions was identified.

To enhance screening, OpenAI’s GPT-5 model was used as a filtering tool. Guided by a structured, literature-based prompt, the model scanned the solutions for explicit or implicit elements related to insurance literacy across four analytical dimensions: understanding of policy terms and coverage, expectation management, knowledge of the claims process and risk assessment. Each dimension was operationalised in the prompt through a short description (e.g. “expectation management” was defined as where inadequate insurance knowledge leads a consumer to form unrealistic expectations about the scope or benefits of their coverage), giving the model concrete decision criteria rather than the bare category label. The prompt instructed the AI model to analyse the data from the customer’s perspective and to flag cases with a clear, textually supported reference to these dimensions, excluding speculative or ambiguous associations where customer reasoning, expectations or decisions could not be identified in the text. The AI model functioned as a screening tool, as all flagged cases were subsequently assessed manually by the researcher to confirm relevance and conceptual fit. Accordingly, the AI-assisted procedure supported case retrieval but did not function as an independent coder. The researcher made the final inclusion decision, requiring a clearly identifiable link to the customer’s reasoning, experiences, decision-making or insurance demand. Cases were excluded where this link was weak, uncertain or speculative or where the dispute concerned genuine procedural, substantive or contractual issues that were unrelated to gaps in insurance literacy.

The data were analysed using an approach following Braun and Clarke’s (2006) six-stage thematic analysis framework, including familiarisation through repeated reading, generation of initial codes, identification of preliminary themes, review of thematic structures, definition and naming of themes and the production of the final analytical narrative. Drawing on literature on insurance and financial literacy, the analysis adopted an initial deductive orientation, deriving starting codes from theory across four dimensions: understanding policy terms and coverage; managing expectations and aligning needs; understanding claims processes and rights; and assessing risks and insurance needs. Coding was conducted manually in ATLAS.ti, and each coded extract was accompanied by a research memo documenting the researcher’s reflexive interpretation. As empirical patterns emerged, the coding framework was iteratively refined, producing subthemes and higher level thematic structures that informed the final analysis.

Screening was conducted iteratively, guided by thematic saturation. To address the possibility that potentially relevant cases were missed by the AI-assisted screening, a subset of recommended solutions outside the flagged pool was revisited during the coding process. Rather than being reviewed against a predetermined sample size, these were assessed until no further key insights emerged, consistent with the saturation logic guiding the broader analytical process. This suggested that further material would not have materially affected the conclusions and offered a preliminary signal, rather than definitive confirmation, that the screening process had not systematically overlooked relevant cases. Following this process, 166 recommended solutions were retained, yielding 282 analytical findings, as individual cases could give rise to multiple observations. The resulting data set was considered sufficiently rich in information to support robust qualitative interpretation.

To enhance transparency and dependability, interpretive decisions were systematically documented in research memos, and the coding framework was grounded in established literature. As the coding and interpretation were conducted by a single researcher, dependability was strengthened by the structured and constrained nature of the AI-assisted screening, the full manual review of all included cases, and the systematic documentation of analytical decisions. External validation was further provided by sharing and discussing the findings with FINE’s staff to ensure contextual and terminological accuracy and to obtain interpretative feedback.

Consumers demonstrated varying levels of competence in recognising risks relevant to their protection needs. In several cases, individuals expressed confidence that existing structures or items were unlikely to fail, indicating an underestimation of gradual or cumulative risks. For example, one consumer justified limited preparedness by stating:

Other consumers framed risk assessment through past performance rather than objective deterioration, as illustrated in a case where the consumer referred to long, trouble-free use to justify expectations of coverage:

Certain decisions also reflected a lack of attention to everyday situational risks. One consumer, for instance, left valuable items in a public area without supervision:

These examples illustrate how risk perception was shaped by subjective judgements (prior functioning, immediate experience or situational assumptions) rather than rational evaluation.

Beyond recognising risks, some consumers struggled to assess how insurance coverage aligns with personal circumstances. In one case, an individual justified expectations of compensation by referring to professional needs:

Collectively, the findings show that consumers experience significant difficulties at the early stages of the insurance lifecycle, particularly in identifying and evaluating risks relevant to their protection needs. As observed in prior research, gradual, cumulative and everyday situational risks are often underestimated, leading to distorted perceptions of likelihood and exposure.

These shortcomings in risk identification carried over into subsequent risk management decisions. Even when potential losses were acknowledged, their significance was assessed primarily in terms of personal or professional impact rather than through careful consideration of risk characteristics, policy scope or contractual conditions. As a result, risk management was often framed in terms of perceived personal consequences rather than actual coverage, producing a divergence between perceived and contractual protection. Overall, insufficient coverage appears to stem not from a single decision but from interrelating behavioural biases, limited insurance literacy and interpretive gaps that shape consumer behaviour at multiple points in the insurance lifecycle.

The analysis identified indications of conceptual misunderstandings regarding how insurance operates. Some individuals regarded premiums as conferring broad entitlement to compensation, independent of contractual criteria. For instance, one consumer argued:

Misunderstandings also emerged in expectations that insurance restores a prior state rather than compensates according to predefined terms:

Uncertainty about distinctions between insurance products also influenced expectations. In one instance, a beneficiary mistakenly assumed that the limitations and provisions of an accident policy would operate just like those of a life insurance policy:

These excerpts demonstrate how consumers’ interpretations often relied on intuitive or experiential reasoning rather than contractual policy text. Expectations were sometimes extended to hypothetical scenarios beyond the event covered, such as a case in which an insured argued:

Together, these observations indicate that consumer misunderstandings arise both at a conceptual level and in relation to specific policy terms. At the conceptual level, insurance is not always understood as a conditional risk-transfer mechanism rather than an entitlement. At the policy level, misunderstandings concern coverage limits, exclusions, and differences between products. Previously formed expectations later resurface at the claims stage, where coverage limitations or denials intensify dissatisfaction. The resulting misalignment reflects not only knowledge gaps but also framing and communication practices that influence how consumers interpret and apply their existing knowledge. Social and experiential factors, including prior experiences and informal comparisons, further reinforce these mental models. Consequently, clearer policy wording or disclosure alone is unlikely to resolve misunderstandings. Enhancing conceptual transparency requires a lifecycle-wide approach addressing how expectations are formed through marketing, service interactions and claims experiences, not isolated interventions at the point of purchase.

The findings also included examples of uncertainty surrounding rights and obligations during both the application for an insurance policy and later in claims processes. Some consumers did not recognise which information must be disclosed when applying for coverage. One individual explained:

Others had difficulties understanding that fulfilling certain procedural requirements was essential for the claims process to proceed. In one case, a substantial delay in submitting medical evidence created challenges in the handling of the claim:

Certain expectations also indicated misconceptions about the burden of proof. One individual argued:

Overall, the findings suggest that some consumers viewed procedures primarily as the insurer’s obligation. This points to persistent difficulties in understanding the shared nature of insurance contracts, where actions of consumers affect entitlement to compensation. As a result, uncertainty about rights and obligations can arise at any stage of the insurance lifecycle (during application, over the course of the policy term or in the claims process) whenever procedural action is required of the consumer.

Understanding rights and responsibilities therefore emerges as a central element of consumer experience across the insurance lifecycle, from purchase to claims handling and policy termination. Consumer difficulties seemed to be driven primarily by information asymmetries surrounding disclosure duties, procedural conditions and claims assessment, rather than by intentional insurer misconduct. Insurance literacy plays a key mediating role throughout the lifecycle, and unclear processes can erode trust even when insurers act within contractual limits. These findings suggest that transparency is most effective when there is a consistent effort to integrate it across all stages of the policy lifecycle. At the same time, continuously reinforcing fundamental knowledge about contract procedures and claims processes is essential to reduce information gaps and maintain trust.

The analysis revealed instances where consumers relied on informal or indirect sources of information instead of referring to policy documents or clarifying uncertainties with insurers. In one case, a consumer openly described depending on interpersonal trust:

Marketing and media messaging sometimes served as reference points for coverage expectations. For example:

There were also cases in which inconsistencies across material types contributed to misunderstandings. One consumer noted:

Together, these findings suggest that consumers’ information-acquisition strategies in insurance rely on trust, assumptions and secondary sources – such as sales representatives, marketing messages or prior experience – rather than detailed engagement with policy documentation. This trust-based decision-making may be understood as a coping response to product complexity, but it is reinforced by lifecycle-wide weaknesses, including inconsistent terminology and disclosures that emphasise benefits over limitations. As a result, formal regulatory compliance at the product design and disclosure stages does not necessarily translate into effective consumer understanding, exposing structural limits of disclosure-based regulatory approaches. Instead, gaps between marketing-driven expectations and contractual realities often persist, particularly where technical language blurs the boundaries of coverage. Overall, the findings indicate that improving insurance literacy requires coherent, lifecycle-wide approaches that go beyond clearer documents, supporting consumers in evaluating, contextualising and reassessing information throughout the entire insurance relationship.

Based on the analysis of alternative dispute resolution cases as presented above, this paper demonstrates how insurance literacy gaps emerged across multiple areas that are essential to both individual financial well-being and broader market functioning. From a consumer protection perspective, these gaps appear as recurring structural weaknesses where the effectiveness of regulatory frameworks depends on an assumed level of consumer understanding that is not always realised in practice. Table 2 synthesises these practical implications by linking empirical observations from consumer disputes to established theoretical explanations.

Although Table 2 analytically distinguishes four dimensions of insurance literacy, they are closely interconnected in practice. Consumers’ ability to identify and manage risks shapes how they interpret insurance products, while constraints in acquiring information reinforce reliance on assumptions, sales narratives and informal sources.

Building on this synthesis, the analysis of consumer disputes shows that limited insurance literacy leads consumers to misjudge risks, form unrealistic expectations regarding coverage and engage insufficiently with policy terms across product selection, contract formation, policy management and claims handling. These gaps reflect not only knowledge deficits but also confidence, motivation and broader social and institutional factors. Rather than being limited to initial product purchase, literacy challenges recur throughout the lifecycle, creating a feedback loop in which interpretations and outcomes shape future expectations and reinforce persistent gaps. Enhancing insurance literacy therefore requires supporting consumers’ ability to access, interpret and apply information, integrating cognitive, behavioural and structural dimensions to strengthen decision-making. As illustrated in Figure 1, this loop operates within the regulatory framework, which shapes, for example, product design, disclosure and distribution through standards for conduct, transparency and product governance. In the EU context, this includes the IDD, POG requirements and standardised disclosure instruments such as IPIDs, which jointly aim to ensure that products meet the needs of defined target markets and that consumers receive clear and comparable information. Within this framework, literacy gaps arise and translate into practical outcomes at every stage of the insurance product lifecycle.

Overall, this paper contributes to the literature by advancing a dynamic, lifecycle-based understanding of insurance literacy as a separate and critical component of financial literacy and human capital, shaping individual financial well-being, trust in financial institutions and participation in insurance markets. By demonstrating that insurance literacy gaps emerge across multiple stages of the insurance product lifecycle rather than being confined to the point of purchase, the findings show how consumers interpret and act upon insurance information. From a methodological perspective, qualitative thematic analysis of real-world alternative dispute resolution cases provides novel insights into misunderstandings, expectation formation and reasoning under actual financial stakes.

From both a regulatory and practical perspective, the findings suggest that while regulation is essential for setting minimum standards, its effectiveness depends on consumers’ ability to understand and process the information provided. Disclosure instruments such as IPIDs do not automatically ensure that key product features are understood. As a result, cognitive asymmetries may persist even when information asymmetries are reduced under the IDD. This indicates that the core limitation is not the availability of information but consumers’ capacity to interpret it. Beyond a certain point, additional disclosure is likely to yield diminishing returns, and expanding information provision alone is therefore unlikely to significantly improve consumer outcomes.

Accordingly, the issue should not be understood purely as one of regulatory compliance on the supply side. Rather, it reflects a broader interaction between product design (including POG requirements), disclosure practices (such as IPIDs and the IDD requiring that information be fair, clear and not misleading) and actual consumer comprehension. Improving regulatory effectiveness therefore requires an integrated approach that aligns these elements. In practical terms, this means combining robust product governance with targeted measures aimed at strengthening consumer understanding, with potential benefits for both financial well-being and trust.

Certain limitations should be acknowledged in interpreting these findings. Because the data set consists of disputes escalated to FINE, the cases may over-represent more complex or motivated consumers and therefore do not reflect the full spectrum of insurance literacy in the general population. Such disputes likely capture only the more severe or consequential misunderstandings, meaning that certain gaps may remain unobserved among consumers who do not pursue formal complaint processes. Dependability was supported through iterative memoing, theoretically grounded coding decisions and external validation. These findings also reflect Finland’s institutional setting. FINE’s dispute resolution process and the country’s approach to IDD implementation may not hold in jurisdictions structured differently. The underlying cognitive and behavioural patterns are likely to have broader relevance, but the specific findings warrant caution when extended elsewhere.

Future research could build on these insights by examining how consumer understanding and decision-making capacity can be strengthened alongside regulatory measures. Quantitative approaches (such as surveys and experiments) could measure the prevalence and impact of specific insurance literacy gaps. Such complementary approaches would deepen theoretical insight and support the development of targeted, evidence-based consumer-protection interventions that complement regulatory efforts and address the limits of supply-side rules alone.

The author gratefully acknowledges Vakuutustiedon Kehittämissäätiö for supporting this research. The funder’s financial support allowed the author to take study leave from his regular duties, facilitating the analysis and writing of this article.

The author confirms that the manuscript was written by the author and not generated by an AI tool or large language model. OpenAI’s GPT-5 was used only as a filtering aid during data screening, limited to automatically flagging potentially relevant texts based on predefined prompts. All analysis and all written content were produced by the author.