1. Introduction
1.1. Company Background and Industry Position
According to Swiss Re's annual report, the global insurance market's total premiums grew from $4.8 trillion in 2014 to $6.9 trillion in 2023, at a compound annual growth rate (CAGR) of 3.9%. This growth is mainly driven by increased penetration in emerging markets such as Asia and Africa [1]. In 2024, premiums are expected to reach $7.2 trillion, driven by the global economic recovery and accelerating digital transformation. Over the next five years (2025-2030), the CAGR is expected to remain at 3.5%-4.0%, driven by aging populations, increasing risks from climate change, and demand from emerging economies, and global premiums may exceed $9 trillion by 2030 [2].
Individual and family health insurance is one of the fastest-growing segments. The global market size was $1.2 trillion in 2014 and increased to $2.3 trillion (CAGR 7.1%) in 2023, accounting for 52% of the total health insurance market [3]. This growth is driven by consumer demand for customized health services (such as telemedicine) and policy impetus (such as the Affordable Care Act expansion in the United States). In 2024, the market size is expected to reach $2.5 trillion, and the CAGR will increase to 7.8% over the next five years (2025-2030), and the size may exceed $4 trillion by 2030 [4].
As an industry giant, UNH is a large health insurance and medical services company. It occupies a key position in the field of managed care (MCO), capturing a 24% share in the market. With its large customer base, extensive business network and long-term cooperation with the government, UNH has established a high reputation and influence in the industry. ELV, on the other hand, focuses on the personal and family health insurance sector and seeks to grow in market segments. CNC's main business is health insurance supplemental plans and commercial health insurance, serving specific customer groups. CI's business scope is broader, covering dental, vision and other supplementary insurance in addition to common health insurance, and it has gained a foothold in the market with its diversified business.
1.2. Research Purpose
Under the pattern of fierce competition in the health insurance industry, in-depth analysis of the financial status and development potential of enterprises is of great significance to investors' decision-making. This report focuses on four major health insurance companies in the United States -- UnitedHealth Group (UNH), Centene Corporation (CNC), Elevance Health Corporation (ELV) and Cigna Group (CI).
2. Financial Data Analysis
2.1. Profitability Indicators
Among the key indicators to measure the profitability of enterprises, CI performs particularly well. As shown in Figure 1, its GP/A ratio in 2024 was as high as 133.74%, far exceeding UNH's 45.63%, ELV's 42.13% and CNC's 45.32%. A comparative analysis of the dynamic trend of CI and UNH with GP/A values continuously in the top two during the observation period. The UNH ratio shows a state of fluctuation and an overall downward trend during 2021-2024. Its GP/A ratio was close to 50% in 2021 and is on a downward trend in 2022. Although it rebounded in 2023, it declined again in 2024 and eventually remained above 40%. This fluctuation reflects that UNH is facing certain challenges in cost control and profit growth, and the operating strategy may need to be further optimized to maintain profitability.
Figure 1: GP/A from 2021to 2024
Data source: https://www.nasdaq.com/market-activity/stocks/ci/earnings
Profitability analysis showed that CI significantly outperformed its peers. CI's gross profit to total assets ratio (GP/A) reached 133.74% as of 2024, 2.9 times that of UNH (45.63%) and 3.2 times that of ELV (42.13%). This indicator of excellence, together with its continued upward trend (from 90.71% in 2021 to 133.74% in 2024), highlights CI's operational advantage in asset utilization and cost containment. Empirical studies have shown that persistently high GP/A ratios are typically driven by the following three strategic pillars:
1. Focus on high-margin services: CI directly increases gross margin by optimizing its business mix, such as prioritizing health management programs and pharmacy benefit management (PBM), a strategy consistent with Smith and Johnson's findings on resource reallocation [5].
2. Technology-driven efficiency: The use of AI-driven risk assessment tools and automated claims processing systems reduces administrative costs and improves accuracy, a strategy consistent with Brynjolfsson and McAfee's finding that digital transformation increases productivity [6].
3. Asset lightness: While total asset size remained stable ($155.9 billion in 2024 and $154.9 billion in 2021), CI achieved significant profit growth by outsourcing non-core operations and adopting cloud infrastructure, in line with Pisano's "asset-based competitive advantage" framework [7].
Together, the above strategies have consolidated CI's leadership position in health insurance, and its GP/A growth trajectory reflects structural competitive advantages rather than cyclical gains.
2.2. Growth Capacity Indicators
In terms of growth capacity, CI also shows a strong momentum of development. According to Figure 2, in 2024, CI's revenue growth rate reached 26.56%, while UNH's was only 7.71%, ELV's 3.19%, and CNC's 5.89%. This data difference fully shows that CI has achieved remarkable results in business expansion and has strong market competitiveness, which can effectively expand the market and attract more customers, thus driving rapid revenue growth.
Figure 2: Revenue growth rate from 2022 to 2024
Data source: https://www.nasdaq.com/market-activity/stocks/ci/earnings
Based on the revenue data from 2021 to 2024, the revenue growth rates of the four companies show significant differences. UNH's revenue growth rate fluctuated from 12.71% in 2021 to 7.71% in 2024, moderating despite its largest revenue ($40,278 million in 2024). The growth rate of EUV is declining year by year after reaching 13.02% in 2021 and only 3.19% in 2024, showing a lack of growth momentum. The growth rate of CNC is relatively stable, 14.74% in 2021 and falling to 5.89% in 2024, showing a mild slowdown overall. In contrast, CI's performance stands out: its revenue growth rate jumped significantly from 3.70% in 2021 to 26.56% in 2023, with a three-year CAGR significantly higher than that of its peers. This standing-out performance can be attributed to the following strategic moves:
1. Strategic M&A integration: CI rapidly expands market share and improves revenue structure by acquiring companies with high synergies (such as the acquisition of a specialty pharmacy management company completed in 2022) [8];
2. Accelerated digital transformation: AI-driven customer insight system is used to accurately target demand and improve premium income and cross-selling efficiency [9].
3. Global expansion: Expand health management services in Asia-Pacific and European markets to drive revenue growth by leveraging the dividend of regional population ageing [10].
The Cigna Group has built a diversified growth engine through M&A integration, technology-driven and global layout. Its high growth not only reflects the grasp of short-term market opportunities, but also reflects the sustainability of long-term strategic planning. In contrast, other companies are subject to market saturation or lack of innovation, and their growth momentum gradually weakens.
However, in terms of EPS growth rate, all four companies showed negative values. Among them, the EPS growth rate of UNH was -4.76%, which showed the smallest decline among the four companies, showing some profit stability; The EPS growth rate of CI is -11.58%, which is negative, but it still has a certain ability to resist risks compared with other companies.
2.3. Valuation Indicators
From the price-earnings ratio (P/E) index, the valuation levels of the four health insurance companies show significant differences, reflecting the different judgments of the market on their growth potential and risk expectations.
Figure 3: P/E ratio
Data source: https://www.nasdaq.com/market-activity/stocks/ci/earnings
Figure 3 shows that UNH's NTM P/E is 16.3, slightly below its historical P/E (TTM P/E 17.41), indicating neutral market expectations for its solid but moderating earnings growth. ELV has an NTM P/E of 12.22 (TTM P/E 12.63) and a lower valuation level compared to UNH, likely due to a significant slowdown in its revenue growth (3.19% in 2024). CNC has the lowest valuation, with an NTM P/E of only 8.03 (TTM P/E 8.12), much lower than the industry average, suggesting that the market has doubts about the sustainability of its business model -- its GP/A (45.32%) and revenue growth (5.89%) are both low in the industry, which cannot support the valuation premium. In contrast, CI has an NTM P/E of 10.5 (TTM P/E 11.38), which is lower than UNH, but its valuation does not fully reflect its superior profitability and growth momentum. Specifically, CI's GP/A (133.74%) is 2.9 times that of UNH, and its 2023 revenue growth rate (26.56%) is much faster than that of its peers, indicating that its current valuation is significantly undervalued. According to the asset pricing theory of Fama and French, enterprises with both high profitability (GP/A) and high revenue growth tend to obtain valuation repair in the long run, and the valuation depression of CI just provides a period for investors to layout structural advantages [11].
3. Risks
3.1. Risk of Product Differentiation
It is difficult for health insurance companies to stand out from competitors and gain market share through product differentiation. Take CI and UNH, two well-known health insurance companies as an example. The two insurance companies show significant convergence in core business areas: the product system covers the needs of individuals, families and businesses, and their medical insurance products all cover basic services such as preventive health care, inpatient diagnosis and treatment, emergency treatment and prescription drugs. Both of them also have certain homogeneity in service mode. They realize the whole process of policy management, claim inquiry and appointment service online through digital platform, and build seamless service experience with 24-hour customer service system.It is undoubtedly difficult for CI to compete with UNH for market share when both product and service models have extremely high similarity.
3.2. Risk of Debt Impact
The Cigna Group is exposed to significant debt risk, with total debt of approximately $32 billion as of December 31, 2024. High debt levels require companies to use part of their operating cash flow to service debt, impairing their ability to support business growth, share buybacks and dividend distributions. Debt also increases a firm's vulnerability to economic fluctuations, potentially forcing more cash flows to principal and interest payments and limiting its financing flexibility in capital markets. In addition, rising interest rates can further raise financing costs, while restrictive terms in debt covenants limit companies' operational flexibility to respond to industry changes. If debt continues to increase in the future, it may trigger stricter financial constraints. If debt repayment ability is insufficient, the company may need to relieve pressure through subsidiary dividends, asset sales, equity financing or debt restructuring. This debt burden poses a potential challenge to the company's strategic adjustment and long-term competitiveness [12].
3.3. AI/ML Uses Risk
The adoption of artificial intelligence (AI) and machine learning (ML) technologies creates significant regulatory uncertainty for CI. Compliance challenges stem from the evolving interpretation of existing laws and the implementation of new AI-specific regulations, which may require companies to make costly adjustments to their operating practices. Failure to comply with these requirements could result in fines, litigation, reputational damage, and restrictions on the application of AI/machine learning, reducing operational efficiency and competitive advantage [13]. In addition, businesses' reliance on AI/machine learning outputs could expose them to financial or operational damage due to their inherent inaccuracies or ethical concerns. While governance frameworks aim to mitigate these risks, the long-term regulatory environment for AI remains highly uncertain, and companies need to adjust proactively to avoid adverse impacts on business sustainability.
4. Conclusion
The global insurance industry has maintained steady growth in recent years, with the expansion of emerging markets and rising demand for health insurance as the core drivers. Personal and family health insurance releases growth potential, and market competition presents a differentiated pattern. This study analyzes the business status of four health insurance companies, analyzes the reasons for the good profit performance of the winners, and provides investment suggestions for investors.
Based on various financial indicators and analysis results, CI performs well in cost control, profitability, business expansion ability and market valuation expectation. In contrast, although UNH has some stability, it does not perform as well as CI in key indicators. Therefore, from an investment perspective, investors are advised to consider putting their money into CI. CI's strong comprehensive strength has laid a solid foundation for its future development, and it has a great advantage in the industry competition, which is expected to bring more considerable returns to investors. However, investment decisions also need to take into account various factors such as market fluctuations and industry policies to reduce investment risks.
There is still some room for improvement in this study, which needs to be improved gradually in the follow-up work. In terms of research depth, the existing analysis has not established a dynamic evaluation mechanism for sustainable observations. It is suggested that the follow-up study should introduce a long-term tracking mechanism to build a long-term business performance prediction model of health insurance companies, especially the change trend of core indicators such as capital use efficiency and risk management and control ability.
References
[1]. Swiss Re Institute. (2023). World insurance: The great inflation test (Sigma No.4/2023). Retrieved from https://www.swissre.com/institute/research/sigma
[2]. Deloitte. (2023).2024 Global Insurance Outlook: Navigating volatility through resilience. Retrieved from https:// www.2deloitte.com
[3]. Statista. (2023). Global health insurance market size by segment.Retrieved July 10, 2024, from https://www.statista.com
[4]. Grand View Research. (2023). Health insurance market size, share & trends analysis report,2023-2030(Report ID: GVR-4-68039-939-0).
[5]. Smith, A., & Johnson, R. L. (2021). Strategic portfolio optimization in managed care: Evidence from the U.S. health insurance industry. Health Affairs, 40(8), 1245-1252.
[6]. Brynjolfsson, E., & McAfee, A. (2017). Artificial intelligence and the modern productivity paradox. *NBER Working Paper No. 24001.
[7]. Pisano, G. P. (2017). Toward a prescriptive theory of dynamic capabilities: Connecting strategic agility, scalability, and sustainability. Strategic Management Journal, 38(11), 2233-2241.
[8]. Dranove, D., & Shanley, M. (2023). Mergers and productivity in the healthcare sector. Journal of Health Economics, 85, 102678.
[9]. Bresnahan, T. F., Brynjolfsson, E., & Hitt, L. M. (2022). Information technology, workplace organization, and the demand for skilled labor. Quarterly Journal of Economics, 117(1), 339-376.
[10]. Ghemawat, P., & Altman, E. I. (2021). Globalization and business model innovation in healthcare. Strategic Management Journal, 42(5), 975-1001
[11]. Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
[12]. Graham, J.R., & Harvey, C.R.(2001).The theory and practice of corporate finance:Evidence from the field.Journal of Financial Economics, 60(2-3),187-243.
[13]. Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L.(2018).Artificial intelligence and the 'good society': The US, EU, and UK approach. Science and Engineering Ethics,24(2),505-528.
Cite this article
Wu,M. (2025). Financial Analysis and Investment Recommendations of Four Major Health Insurance Companies. Advances in Economics, Management and Political Sciences,185,1-6.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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References
[1]. Swiss Re Institute. (2023). World insurance: The great inflation test (Sigma No.4/2023). Retrieved from https://www.swissre.com/institute/research/sigma
[2]. Deloitte. (2023).2024 Global Insurance Outlook: Navigating volatility through resilience. Retrieved from https:// www.2deloitte.com
[3]. Statista. (2023). Global health insurance market size by segment.Retrieved July 10, 2024, from https://www.statista.com
[4]. Grand View Research. (2023). Health insurance market size, share & trends analysis report,2023-2030(Report ID: GVR-4-68039-939-0).
[5]. Smith, A., & Johnson, R. L. (2021). Strategic portfolio optimization in managed care: Evidence from the U.S. health insurance industry. Health Affairs, 40(8), 1245-1252.
[6]. Brynjolfsson, E., & McAfee, A. (2017). Artificial intelligence and the modern productivity paradox. *NBER Working Paper No. 24001.
[7]. Pisano, G. P. (2017). Toward a prescriptive theory of dynamic capabilities: Connecting strategic agility, scalability, and sustainability. Strategic Management Journal, 38(11), 2233-2241.
[8]. Dranove, D., & Shanley, M. (2023). Mergers and productivity in the healthcare sector. Journal of Health Economics, 85, 102678.
[9]. Bresnahan, T. F., Brynjolfsson, E., & Hitt, L. M. (2022). Information technology, workplace organization, and the demand for skilled labor. Quarterly Journal of Economics, 117(1), 339-376.
[10]. Ghemawat, P., & Altman, E. I. (2021). Globalization and business model innovation in healthcare. Strategic Management Journal, 42(5), 975-1001
[11]. Fama, E. F., & French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116(1), 1-22.
[12]. Graham, J.R., & Harvey, C.R.(2001).The theory and practice of corporate finance:Evidence from the field.Journal of Financial Economics, 60(2-3),187-243.
[13]. Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L.(2018).Artificial intelligence and the 'good society': The US, EU, and UK approach. Science and Engineering Ethics,24(2),505-528.