Conventionally, insurance penetration is measured as total insurance premium as a percentage of GDP. While useful as a broad indicator of the insurance sector’s relative size, this is, at best, a rudimentary measure of insurance protection. It captures the volume of insurance spending in relation to the economy, but says little about how many people, households, businesses, assets, or economic activities are actually protected.
This raises a fundamental question: does insurance penetration measure the magnitude of protection, or merely the volume of insurance business transacted during a financial year? The answer is possibly the latter. A high penetration ratio may reflect premium size rather than the depth or breadth of protection. Premium volumes can rise with expensive policies, high-value risks, or large premiums from corporates and business houses, without necessarily translating into widespread insurance coverage.
India’s health insurance sector in 2024–25 provides a telling illustration. Group health insurance accounted for only 13.05 lakh policies, yet generated a substantial Rs. 61,434.68 crore in premium, covering as many as 2,751.01 lakh lives. In contrast, the individual/retail segment comprised 251.85 lakh policies, generated Rs. 46,611.39 crore in premium, but covered only 601.46 lakh lives. (Source IRDAI Annual Report 2024-25 )
The contrast is revealing: premium volume alone does not adequately capture the extent, reach, or depth of insurance protection. What is needed is a more nuanced measure—one that moves beyond premium size and captures the actual protection afforded to individuals, households, business entities, and assets.
The figures clearly show how aggregate premium volumes can be significantly influenced by business concentration in the group/corporate segment, rather than merely by the number of policies or lives covered.
Another important issue relates to the choice of GDP as the denominator. While GDP is a useful measure of economic output, its suitability for measuring the insurance protection gap is less evident. GDP does not necessarily reflect the underlying exposure of individuals, businesses and assets to morbidity and mortality risks, property and agricultural losses, or natural catastrophes. This raises an important question: can GDP, by itself, provide an adequate and meaningful basis for assessing the extent of underinsurance across such diverse and fundamentally different risk exposures?.
Premium volume can also be distorted by price, particularly in health insurance, where inflation and rising medical costs can increase premium income without correspondingly increasing the number of people protected or the level of cover. Adequacy of sum insured is also not captured in this measurement. A 5 lakh cover means a person is insured, but does that mean he is adequately covered, especially when 10 days in a corporate hospital can cost 10 lakh or more?
A country may show high insurance penetration or a large volume of insurance business even when coverage remains concentrated among a relatively small, affluent segment of the population. Such aggregate measures may therefore conceal significant disparities in access to insurance, with lower-income and financially vulnerable groups remaining substantially uninsured. In this sense, high insurance penetration does not necessarily imply a broad or equitable spread of insurance protection across the population; rather, the measure may be highly skewed, as is arguably the case in India.
This limitation is particularly important for life insurance, where reported business volume may include a wide range of products that combine risk protection with savings and investment components. Consequently, a penetration figure based primarily on premiums or insurance business volume does not necessarily indicate the extent of pure mortality-risk protection available to the population. It may therefore overstate the effective level of life-risk coverage, since the investment or savings component embedded in many life insurance products can constitute a substantial part of the reported business. A more meaningful assessment of the life insurance protection gap would thus need to distinguish pure risk protection from savings- and investment-oriented insurance products.
In a country like India, public health programmes, social security schemes and other risk-pooling mechanisms—such as Ayushman Bharat PM-JAY, CGHS, ESIC and ECHS—provide significant health protection without being reflected in commercial health insurance premiums. Consequently, conventional measures of insurance penetration may understate the extent of effective health protection available to the population.
Identical penetration levels across countries do not necessarily tell the same story or indicate comparable levels of protection or coverage. Significant disparities may exist in both the proportion of the population covered and the adequacy of that coverage. Moreover, a rise in the penetration ratio does not necessarily narrow the protection gap; the gap may remain unchanged if the increase is driven primarily by higher insurance prices rather than by broader or more adequate coverage.
What is the way forward—–?
This calls for measuring insurance penetration holistically through an ( already established) Multidimensional Insurance Penetration Index (IPI), going beyond the conventional premium-to-GDP metric. The index could capture six critical dimensions: The last dimension i.e. Community Acceptability is added by the author based on his research work.
- Coverage – the proportion of the population, assets, crops and businesses that are insured.
- Adequacy – the extent to which the sum insured adequately reflects the underlying economic exposure or potential loss.
- Accessibility – the geographical, physical and digital reach of insurance products and services.
- Affordability – the premium burden relative to household or business income and the capacity to pay.
- Claims Effectiveness – not merely the claim settlement ratio, but also the efficacy, timeliness, transparency and customer satisfaction associated with claims settlement.
- Community Acceptability – the extent to which insurance solutions are understood, trusted and acceptable to the communities they serve, including whether the manner in which the protection is delivered aligns with local needs, preferences and cultural contexts. This is particularly important in health insurance, where health is not merely an individual concern but, fundamentally, a community conundrum.
Such a multidimensional approach would shift the focus from simply measuring how much insurance is sold to assessing how meaningfully insurance protection reaches and serves society. Such an index would measure the quality of insurance penetration, not merely its size. The premium-to-GDP measures insurance market depth, whereas true insurance penetration should measure societal risk protection
Multidimensional Insurance Penetration Index can provide a more comprehensive assessment of insurance development than conventional premium-based measures alone. It may comprise the following constituent dimensions:
- Premiums/GDP – Economic Penetration: measures the contribution of insurance premiums relative to the size of the economy and indicates the overall economic penetration of insurance vis-à-vis GDP .
- Premiums per Capita – Insurance Density: captures average premium expenditure per person and indicates the intensity of per person or capita insurance consumption.
- Population Covered – Coverage Penetration: measures the proportion of the relevant population, lives, properties or other insurable units actually covered by insurance. The relevant population means a population, lives, properties or any insurable units have economic and can be legally insured.
- Sum Insured/GDP – Protection Depth: indicates the quantum of financial protection provided by insurance relative to the size of the economy, thereby going beyond premium volumes to assess the depth of protection.
- Claims/Premiums – Utilisation: reflects the extent to which policyholders actually utilise insurance services. A low ratio, however, does not necessarily imply low insurance value, as utilisation may be constrained by lack of awareness, limited information, affordability issues, or complex claims procedures.
- Rural and Underserved Population Coverage – Inclusiveness: measures the extent to which insurance reaches and is effectively accessed by rural, low-income and otherwise underserved populations.
- Community Acceptability – will measure the trust of the community in the overall delivery mechanism.
Taken together, these dimensions move the assessment of insurance penetration from a narrow measure of premium volume to a broader evaluation of the reach, depth, utilisation and inclusiveness of insurance protection.
The time has come to move away from “premium penetration” to “protection penetration.” The underlying framework would measure three dimensions: In health insurance, we will try to understand coverage penetration, which will shed light on how many people/lives are actually insured. That is, the proportion of lives requiring health protection that are actually covered.
Population Insurance coverage = Number of people with effective (the word effective here denotes adequacy of the sum insured) insurance cover ÷ Total population × 100; this measure gives the Percentage of the population with effective health insurance coverage, thereby indicating the number of people who are actually protected.
Adequacy of Coverage measures the extent to which an individual’s insurance protection is sufficient to meet the underlying financial exposure. The Protection Adequacy Ratio (PAR) may be defined as the ratio of the actual sum insured to the estimated financial exposure. Its precise formulation will vary by line of business. For health insurance, for example, it could be measured as the average or median sum insured relative to the estimated catastrophic or financially stressful healthcare expenditure an individual or household faces.
Accordingly, a logically designed measure of the protection gap can provide a more meaningful assessment of the depth and quality of insurance coverage than conventional measures such as premium-to-GDP or insurance penetration ratios. Premium/GDP measures the size of the insurance market, but does not necessarily indicate whether the underlying economic or financial risks are adequately protected.
The Protection Gap can therefore be defined as:
Protection Gap = Total Economic/Financial Exposure − Insured Exposure
Correspondingly, the Protection Coverage Ratio can be expressed as:
Protection Coverage Ratio = (Insured Exposure ÷ Total Insurable Exposure) × 100
This approach shifts the focus from the volume of insurance purchased to the extent of risk actually protected, thereby providing a more meaningful measure of the adequacy, depth and effectiveness of insurance coverage.
We may distinguish insurance penetration, insurance coverage, and insurance protection as three related but fundamentally different concepts.
Insurance penetration refers to the volume of insurance business written in relation to the country’s GDP. Insurance coverage refers to the number of people, properties, or other assets with economic value that are insured. Insurance protection, however, goes a step further: it reflects the extent to which insurance actually protects or covers the underlying economic risk.
A hypothetical example illustrates the distinction. Suppose Country A has 3% insurance penetration but 70% protection coverage, while Country B has 7% insurance penetration but only 50% protection coverage. At first glance, Country B may appear to be better insured because its insurance penetration is more than twice that of Country A. However, this can be misleading. Despite its lower penetration, Country A protects against a much larger share of underlying risks.
Thus, higher insurance penetration does not necessarily mean greater financial protection. A country may have a relatively large insurance market in relation to its GDP while leaving a substantial portion of its underlying risks uninsured. Conversely, a country with lower penetration may achieve significantly higher protection of its economic assets and population. Ultimately, the extent of risk actually protected, rather than insurance penetration alone, better indicates a country’s financial resilience.
The term “protection gap” is commonly used in the context of catastrophic risks to describe the difference between the economic losses caused by an event and the portion of those losses covered by insurance. The concept of a “health protection gap,” however, is defined rather differently. It is often associated with the financial burden borne directly by individuals, with out-of-pocket (OOP) healthcare expenditure frequently used as a proxy for, or an indicator of, the health protection gap. Catastrophic Health Expenditure (CHE) is often used as an indicator of the health protection gap (HPG), particularly the financial burden arising from inadequate health coverage. According to the WHO, catastrophic health expenditure occurs when a household’s out-of-pocket spending on healthcare exceeds a specified proportion of its available resources, potentially compromising its ability to meet basic needs. Traditionally, CHE was defined as health expenditure exceeding 40% of a household’s capacity to pay after accounting for subsistence needs.
The health protection gap is increasingly defined not merely by the uninsured cost of healthcare, but by the financially stressful out-of-pocket expenditure (OOPE) households incur and the likely cost of treatment forgone because it is unaffordable.OOPE becomes financially stressful when a household is compelled to cut back on essential or discretionary expenditure—such as food, education, or other household needs—to meet rising medical expenses. Importantly, even when households pay medical costs from savings, the expenditure may still be financially stressful, as it erodes the household’s financial resilience and capacity to meet future needs.
Thus, the health protection gap captures not only the healthcare expenses households cannot afford, but also the financial hardship and foregone care resulting from inadequate health protection. If we rely solely on OOPs (out-of-pocket expenditure), we risk overstating the size of the Health Protection Gap (HPG). Conversely, if we fail to account for the costs of foregone or delayed treatment due to affordability and accessibility constraints, we may understate the true magnitude of the HPG. As a result, we find that financially stressful income depends on income level. The higher the income, the lower the financially stressful income, and vice versa.
Is OOPS a Good Proxy for the Health Protection Gap (HPG)?
The answer is no. Out-of-pocket spending (OOPS) is an important indicator of healthcare financing, but it is neither a comprehensive nor an adequate proxy for the Health Protection Gap (HPG).
First, OOPS captures only the expenditure incurred by people who actually access and pay for healthcare. It does not capture healthcare forgone because services are geographically inaccessible or because individuals cannot afford treatment. Consequently, people who need healthcare but never seek or receive it because of financial or physical barriers are effectively invisible in OOPS data. This creates a significant risk of underestimating the true magnitude of the HPG.
Similarly, Catastrophic Health Expenditure (CHE) is not, by itself, an appropriate measure of HPG. CHE focuses on the financial burden households face when healthcare expenditure crosses a defined threshold relative to their income or consumption. Like OOPS, however, it largely overlooks the unmet healthcare needs of those who forgo treatment because it is inaccessible or unaffordable.
Thus, both OOPS and CHE provide valuable insights into the financial burden of healthcare, but neither fully captures the unmet demand, deferred treatment and financial vulnerability that constitute the broader Health Protection Gap. A meaningful assessment of HPG therefore needs to go beyond expenditure-based indicators and incorporate healthcare needs that remain unmet because of lack of access, affordability and adequate financial protection.
The main function of any health system should be to develop a health financing system that protects the population against the financial risks associated with ill health. This financial risk often turns into catastrophic health expenditure and pushes the sufferers into a debt trap.
Even today, on average, 63 million people fall into a debt trap because they lack financial protection for their healthcare needs.
The Swiss Re Institute (2024) estimates the global annual insurance protection gap at USD 1.83 trillion, spanning four major risk areas: health (USD 940 billion), mortality (USD 414 billion), natural catastrophes (USD 385 billion), and crop insurance (USD 77 billion).
Authored by:
Prof(Dr) Abhijit Chattoraj – Chartered Insurer
