The average market risk premium in the United States decreased slightly to 5.5 percent in 2023. This suggests that investors demand a slightly lower return for investments in that country, in exchange for the risk they are exposed to. This premium has hovered between 5.3 and 5.7 percent since 2011. What causes country-specific risk? Risk to investments come from two main sources. First, inflation causes an asset’s price to decrease in real terms. A 100 U.S. dollar investment with three percent inflation is only worth 97 U.S. dollars after one year. Investors are also interested in risks of project failure or non-performing loans. The unique U.S. context Analysts have historically considered the United States Treasury to be risk-free. This view has been shifting, but many advisors continue to use treasury yield rates as a risk-free rate. Given the fact that U.S. government securities are available at a variety of terms, this gives investment managers a range of tools for predicting future market developments.

Market risk premiums (MRP) measure the expected return on investment an investor looks to make. For potential investors looking to add to their portfolio, the perfect scenario for a risk-based investment would be a high rate of return with as small a risk as possible. There are three main concepts to MRP’s, including required market risk premiums, historical market risk premiums and expected market risk premiums. United Kingdom shows little return for risk Europe wide, Finland had one of the lowest MRP alongside Poland and Germany. Ukraine had average risk premiums of 22.6 percent in 2024. Having a lower market risk premium may seem bad, but for countries such as the UK and Germany where rates have been consistent for several years, it is because the market is stable as an environment for investment. Risk free rates Risk free rates are closely associated to market risk premiums and measure the rate of return on an investment with no risk. As there is no risk associated, the rate of return is lower than that of an MRP. Average risk free rates across Europe are relatively low.

Market risk premiums (MRP) measure the expected return on investment an investor looks to make. For potential investors looking to add to their portfolio, the perfect scenario for a risk-based investment would be a high rate of return with as small a risk as possible. There are three main concepts to MRP’s, including required market risk premiums, historical market risk premiums and expected market risk premiums. In 2024, average market risk premiums in Germany stood at 5.6 percent. MRP in Europe As of 2024, Germany had one of the lowest average market risk premium in Europe. At the same time, market risk premiums in Ukraine were almost twice as high due to the risk of investment involved. Risk free rates Risk free rates are closely associated to market risk premiums and measure the rate of return on an investment with no risk. As there is no risk associated, the rate of return is lower than that of an MRP. Average risk free rates across Europe were relatively low in 2024. The risk free rate of investment in Germany was less than three percent as of 2024.

Split into three categories (required, historical, expected), market risk premiums measure the rate of return investors expect on an investment over the risk that investment holds. In Europe, average market risk premiums (MRP) sit between five and ten percent.

Greece sees hike in MRP

Although it has a relatively high market risk premium, Greece has seen its rates significantly decrease since 2020. Greece also saw a higher than average return rate on risk free investments. The same correlation can be seen with Europe’s less risky countries for investment. With Germany seeing some of the lowest market risk premiums and risk free returns in Europe.

Required, historical and expected

Separating the three types of market risk premiums is straightforward. Required MRP’s differ between investors, as approaches to investment change and measure the rate of return needed for an investment to be made. Expected premiums look at the rate of return, and what they are calculated to come out as, while historical MRP’s look back over a period at the average rate of return that investors previously got in the past.

Average market risk premiums (MRP’s) in Sweden have fluctuated between 2011 and 2024. As of 2024, the average market risk premium in Sweden amounted to *** percent. Compared to other countries in Europe, Sweden’s average MRP was relatively low. Similar countries included the Netherlands and Norway, among others. Required, historical and expected Separating the three types of market risk premiums is straightforward. Required MRP’s differ between investors, as approaches to investment change, and measure the rate of return needed for an investment to be made. Expected premiums look at the rate of return, and what they are calculated to come out as, while historical MRP’s look back over a period at the average rate of return that investors previously got in the past. Risk-free rates Risk-free rates are closely associated to market risk premiums and measure the rate of return on an investment with no risk. As there is no risk associated, the rate of return is lower than that of an MRP. Average risk-free rates across Europe (with some exceptions) were relatively low in 2022. As of 2023, The average risk-free rate of investment in Sweden was roughly *** percent, the highest ratio recorded since 2015.

The average market risk premium used in Denmark fluctuated between 2011 and 2024. As of 2024, the market risk premium in the country reached a value of 5.8 percent, lower than the previous year.

The average market risk premium in South Africa increased to 8.3 percent in 2024. Market premium risk represents the difference between return on equities and a risk-free investment, which is normally associated with short-term government bonds. For comparison, the U.S. market premium risk amounted to 5.5 percent in the same year. Risk-free rate Most analysts consider the U.S. treasury rate to be the risk-free rate for the term of their investment, assuming the United States government will not default. Just as consumers in the Unites States get a credit rating, agencies such as Standard & Poor’s rate countries’ credit risks. Using these data, analysts compute the country-specific default risk, which in turn has an influence on the value of risk-free rate. What influences the return on equities? The economic factors such as political stability in a country, inflation rate, level of indebtment, trade deficit and investments have an influence on the activities of companies and their valuation on the stock exchanges. Apart from the economic cycle, the company’s operations itself, which are reflected in the results published in the financial reports, can boost or diminish the stock returns.

The average market risk premium in Canada was 5.2 percent in 2024. This means investors demanded an extra 5.2 Canadian dollars on a 100 Canadian dollar investment. This extra cost should compensate for the risk of an investment based in Canada. What causes risk? As far as country-specific factors are concerned, macroeconomic trends can cause risk. For example, the inflation rate in relation to other countries can change the relative value of an investment. Lower inflation in Canada could weaken the Canadian dollar, reducing the value of Canadian assets in terms of another currency, such as the euro or U.S. dollar. The Canadian context As a country, Canada has a fairly high national debt. Some economists point to this as an increased default risk, since debt servicing can become costly. However, most investors agree that Canada, as an advanced economy, is creditworthy and not at risk of defaulting. A better measure is to look at Canada’s risk premium in the context of interest rates from other countries. These deposit rates can be used as a baseline for the market risk premium of other countries, though they do not include all the factors that have been used to calculate this statistic.

Indonesia Domestic Government Bonds Trading: Secondary Market by Sector: Frequency: < 5 Years data was reported at 8,679.000 Unit in Mar 2025. This records a decrease from the previous number of 8,981.000 Unit for Feb 2025. Indonesia Domestic Government Bonds Trading: Secondary Market by Sector: Frequency: < 5 Years data is updated monthly, averaging 1,506.000 Unit from Jan 2008 (Median) to Mar 2025, with 145 observations. The data reached an all-time high of 16,495.000 Unit in Sep 2020 and a record low of 314.000 Unit in Mar 2013. Indonesia Domestic Government Bonds Trading: Secondary Market by Sector: Frequency: < 5 Years data remains active status in CEIC and is reported by Directorate General of Budget Financing and Risk Management. The data is categorized under Indonesia Premium Database’s Financial Market – Table ID.ZB007: Ministry of Finance: Government Securities: Trading in Secondary Market.

Indonesia Domestic Government Bonds Trading: Secondary Market by Sector: Volume: < 5 Years: Percentage data was reported at 44.640 % in Mar 2025. This records a decrease from the previous number of 47.110 % for Feb 2025. Indonesia Domestic Government Bonds Trading: Secondary Market by Sector: Volume: < 5 Years: Percentage data is updated monthly, averaging 31.810 % from Jan 2008 (Median) to Mar 2025, with 145 observations. The data reached an all-time high of 82.860 % in Jan 2024 and a record low of 8.330 % in Mar 2013. Indonesia Domestic Government Bonds Trading: Secondary Market by Sector: Volume: < 5 Years: Percentage data remains active status in CEIC and is reported by Directorate General of Budget Financing and Risk Management. The data is categorized under Indonesia Premium Database’s Financial Market – Table ID.ZB007: Ministry of Finance: Government Securities: Trading in Secondary Market.

Graph and download economic data for Term Premium on a 10 Year Zero Coupon Bond (THREEFYTP10) from 1990-01-02 to 2025-05-30 about term premium, 10-year, bonds, and USA.

The yield on Canada 10Y Bond Yield rose to 3.36% on June 9, 2025, marking a 0.02 percentage point increase from the previous session. Over the past month, the yield has edged up by 0.15 points, though it remains 0.15 points lower than a year ago, according to over-the-counter interbank yield quotes for this government bond maturity. Canada 10-Year Government Bond Yield - values, historical data, forecasts and news - updated on June of 2025.

The student accident insurance market is experiencing robust growth, driven by increasing awareness of the need for comprehensive coverage among parents and educational institutions. A rising number of extracurricular activities and sports participation among students contribute significantly to this demand. While precise market sizing data is unavailable, based on industry reports and observed trends in similar insurance sectors, we can estimate the 2025 market size to be approximately $2.5 billion USD. Assuming a conservative Compound Annual Growth Rate (CAGR) of 5% over the forecast period (2025-2033), the market is projected to reach approximately $3.9 billion USD by 2033. Key market drivers include rising healthcare costs, increasing parental concerns about student safety, and mandatory insurance requirements implemented by some schools and universities. Significant trends shaping the market include the increasing adoption of digital platforms for policy purchasing and management, personalized insurance plans catering to specific student needs, and the expansion of coverage options beyond basic accident protection to include emergency medical evacuation and repatriation services. However, restraining factors like high insurance premiums, lack of awareness in certain regions, and competition from alternative risk management solutions could potentially hinder market growth. The market is segmented by coverage type (e.g., basic accident, comprehensive), distribution channel (direct sales, brokers), and geography. Major players like Old Republic Insurance, Chubb, and Allianz, along with specialized providers such as StudyInsured and Insuremykids, are actively competing to capture market share through product innovation and strategic partnerships.

Dataset Description: Insurance Claims Prediction

Introduction: In the insurance industry, accurately predicting the likelihood of claims is essential for risk assessment and policy pricing. However, insurance claims datasets frequently suffer from class imbalance, where the number of non-claims instances far exceeds that of actual claims. This class imbalance poses challenges for predictive modeling, often leading to biased models favoring the majority class, resulting in subpar performance for the minority class, which is typically of greater interest.

Dataset Overview: The dataset utilized in this project comprises historical data on insurance claims, encompassing a variety of information about the policyholders, their demographics, past claim history, and other pertinent features. The dataset is structured to facilitate predictive modeling tasks aimed at accurately identifying the likelihood of future insurance claims.

Key Features: 1. Policyholder Information: This includes demographic details such as age, gender, occupation, marital status, and geographical location. 2. Claim History: Information regarding past insurance claims, including claim amounts, types of claims (e.g., medical, automobile), frequency of claims, and claim durations. 3. Policy Details: Details about the insurance policies held by the policyholders, such as coverage type, policy duration, premium amount, and deductibles. 4. Risk Factors: Variables indicating potential risk factors associated with policyholders, such as credit score, driving record (for automobile insurance), health status (for medical insurance), and property characteristics (for home insurance). 5. External Factors: Factors external to the policyholders that may influence claim likelihood, such as economic indicators, weather conditions, and regulatory changes.

Objective: The primary objective of utilizing this dataset is to develop robust predictive models capable of accurately assessing the likelihood of insurance claims. By leveraging advanced machine learning techniques, such as classification algorithms and ensemble methods, the aim is to mitigate the effects of class imbalance and produce models that demonstrate high predictive performance across both majority and minority classes.

Application Areas: 1. Risk Assessment: Assessing the risk associated with insuring a particular policyholder based on their characteristics and historical claim behavior. 2. Policy Pricing: Determining appropriate premium amounts for insurance policies by estimating the expected claim frequency and severity. 3. Fraud Detection: Identifying fraudulent insurance claims by detecting anomalous patterns in claim submissions and policyholder behavior. 4. Customer Segmentation: Segmenting policyholders into distinct groups based on their risk profiles and insurance needs to tailor marketing strategies and policy offerings.

Conclusion: The insurance claims dataset serves as a valuable resource for developing predictive models aimed at enhancing risk management, policy pricing, and overall operational efficiency within the insurance industry. By addressing the challenges posed by class imbalance and leveraging the rich array of features available, organizations can gain valuable insights into insurance claim likelihood and make informed decisions to mitigate risk and optimize business outcomes.

Up until 2018, the average risk-free rate in Germany remained relatively stable at approximately 1.4 percent. The risk-free rate is a theoretical rate of return of an investment with zero risk. This rate represents the minimum interest an investor would expect from a risk-free investment over a period. It is important to remember that the risk-free rate is only theoretical as all investments carry even the smallest of risks. As of 2024, the risk-free rate in Germany was 2.7 percent. Risk free rates in Europe A higher risk-free rate illustrates that even with a so-called "zero risk" investment, investors would want a higher return because of the countries associated investment risks. In Europe, Ukraine and Turkey were among the countries with relatively higher average risk-free rates in 2024 compared to other European countries. The majority of European countries have RF rates under four percent in 2024. Market risk premiums Risk free rates reflect market risk premiums (MRP) with Germany displaying low MRP compared to other European countries. Split into three categories (required, historical, expected), market risk premiums measure the rate of return investors expect on an investment over the risk that investment holds. In Europe, average market risk premiums (MRP) sit between five and ten percent. During the last ten years, Germany has seen slight increase in market risk premiums.

The US homeowners insurance market, a significant segment of the broader property and casualty insurance sector, is experiencing steady growth, driven by factors such as rising home values, increasing construction activity, and a growing awareness of the importance of property protection. The market's size, while not explicitly stated, can be reasonably estimated based on the global CAGR of 3% and the presence of major insurers like State Farm, Allstate, and Farmers Insurance, which command substantial market share domestically. Given the size and economic activity of the US, the US market likely represents a considerable portion of the global market. The market is segmented by insurance type (HO-1 through HO-8, reflecting varying levels of coverage), and distribution channels (independent advisors, affiliated agents, direct sales, and online channels), each exhibiting unique growth trajectories. The increasing adoption of online channels and the rise of Insurtech companies like Lemonade are transforming distribution, fostering greater competition and potentially driving down premiums in certain segments. However, factors like increasing natural disaster frequency and severity, along with escalating construction costs, are placing upward pressure on premiums, representing a significant restraint on market growth. This necessitates insurers to adopt sophisticated risk assessment models and leverage advanced technologies for loss prevention and claims management. The competitive landscape is highly fragmented, with both established players and newer entrants vying for market share. Established players like State Farm and Allstate benefit from strong brand recognition and extensive distribution networks. However, Insurtech companies are disrupting the market with their digitally-driven models, appealing to tech-savvy consumers seeking convenience and potentially lower costs. This competitive dynamic is driving innovation and efficiency across the sector, leading to better customer experiences and more tailored insurance products. Future growth is expected to be further influenced by regulatory changes, technological advancements in risk management and fraud detection, and the overall economic health of the US. Analyzing these elements provides a comprehensive view of the opportunities and challenges that characterize the dynamic US homeowners insurance market. Recent developments include: Direct-to-consumer home insurance technology company Kin Insurance is going public through a reverse merger with Omnichannel Acquisition Corp. The agreement values Kin Insurance at roughly $1.03 billion. Kin's technology-first approach enables customers to insure homes online within minutes., Porch Group, the Seattle-based home services software company, completed its $100 million acquisition of homeowners of America Inc in 2020. Their plan is to expand aggressively across the vast majority of states. Porch cut its net loss in half in 2020, to $51.6 million, from $103 million in 2019. Notable trends are: InsurTech in the US Homeowner's Insurance.

The United Kingdom motor insurance market, valued at approximately £23.44 billion in 2025, is projected to experience steady growth, exhibiting a Compound Annual Growth Rate (CAGR) of 4.16% from 2025 to 2033. This growth is driven by several factors. The increasing number of vehicles on the road, fueled by population growth and economic activity, contributes significantly to higher demand for insurance coverage. Furthermore, stricter regulations around mandatory insurance and a rising awareness of the financial implications of accidents are boosting market penetration. Technological advancements, such as telematics and AI-powered risk assessment, are also influencing market dynamics. These technologies enable insurers to offer more personalized and affordable premiums, leading to improved customer satisfaction and increased market participation. The market is segmented by product type (Third-Party, Third-Party Fire and Theft, Comprehensive) and distribution channel (Direct, Agency, Banks, Others). The comprehensive insurance segment, offering the most extensive coverage, is likely to dominate the market, while digital distribution channels are expected to gain traction due to their convenience and cost-effectiveness. Competition amongst established players such as The Prudential Assurance Company Limited, Aviva, Allianz Insurance PLC, and Zurich Assurance Ltd remains intense, stimulating innovation and driving efficiency improvements. The market faces certain restraints, primarily the economic climate and its impact on consumer spending. Periods of economic downturn could lead to reduced disposable income, potentially affecting insurance purchase decisions. Furthermore, the increasing frequency and severity of fraudulent claims pose a challenge to insurers, requiring them to implement robust fraud detection mechanisms. Nonetheless, the long-term outlook for the UK motor insurance market remains positive, underpinned by consistent growth in vehicle ownership, evolving consumer preferences, and technological innovation. The market's performance will continue to depend on factors like economic stability, legislative changes, and the ability of insurers to adapt to changing customer demands and technological advancements. The expansion of telematics-based insurance, offering personalized premiums based on driving behaviour, presents a significant growth opportunity for insurers in the coming years. Recent developments include: Feb 2022: For an initial payment of GBP 47.5 million, AXA UK&I purchased the renewal rights to Ageas UK's commercial operations. This acquisition reinforces AXA's growth strategy and dedication to its commercial business clients and broker alliances, particularly in the SME and Schemes market sectors. About 100 Ageas UK personnel will transfer to AXA Commercial as part of the arrangement to provide continued support and service delivery., Jan 2022: The cost of a comprehensive car insurance policy in Britain is expected to be volatile this year after rising 5% in the final quarter of 2021 as more drivers took to the roads to ease COVID-19 curbs. Motorists must pay GBP 539 (USD 734.06) on average for their comprehensive car insurance premiums.. Key drivers for this market are: Data Privacy Regulations, Business Interruption. Potential restraints include: Complexity and Lack of Understanding, Cost of Coverage. Notable trends are: High Volatility in Car Insurance Premiums During the Past Few Years.

Shifting claims costs have incited revenue volatility in the Life Insurance industry. Insurers have begun to bounce back after navigating difficult business interruption incidents during the pandemic. Slowing claims payouts as pandemic-related deaths decelerate have allowed many life insurers to regain their footing and claw back some revenue. Additionally, insurers' investment returns have recovered as equity markets have ticked upwards in recent years. Life insurance providers protect against financial hardships from death, disability, major illness or injury. Loss of income can cause significant financial problems. Following the findings of the Royal Commission into Misconduct in the Banking, Superannuation and Financial Services Industry, all four major banks sold their life insurance businesses. Over the past five years, higher cancellation rates and policy lapses have hammered premium income. Potential policyholders have faced climbing inflation and have had to make hard financial decisions. When choosing a life insurance policy, some households and businesses have decided that times are too tough, and have instead prioritised other areas of their budget. Consumers’ broad awareness of life insurance policy benefits has also taken a hit, as younger people are failing to provide premium revenue at the same rate as previous generations. Industry revenue is expected to have sunk at an annualised 5.9% over the five years through 2024-25, to $31.8 billion, as retail disability insurance policies have performed poorly and regulatory changes have weakened revenue streams. However, recent premium price hikes and decelerating claims payouts have helped buoy revenue in recent years, slightly offsetting overall industry declines. Demand-side inflationary concerns are currently weighing on the industry’s performance, with revenue anticipated to falter 2.4% in 2024-25. The industry’s profitability relies heavily on investment revenue. In the coming years, insurers will remain at the whim of market conditions. Stronger investment returns and the ongoing need for life insurance products will support a modest upturn in premium income and revenue. Additionally, recovering household discretionary incomes will support industry revenue, which is set to grow at an annualised 2.3% over the five years through 2029-30, to reach $35.6 billion.

The dataset consists of 68 observations (rows) and 24 variables (columns). It contains information about opinions issued on IFRS 17 implementation challenges. The dataset includes details about the opinion issuer (e.g., whether they are a practitioner, expert, researcher, or teacher), as well as binary indicators for various IFRS 17-related issues. These issues include problems with annual cohorts, the treatment of onerous contracts, discount rate calculation methods, the Premium Allocation Approach (PAA), first-time implementation difficulties, risk adjustment for non-financial risk, IT system challenges, and interactions between IFRS 9 and IFRS 17. Each issue is coded as “1” if mentioned in the opinion and “0” otherwise. The dataset allows for analyzing how different types of opinion issuers perceive IFRS 17 challenges and which problems are most frequently reported.Genaral Variables1. Company – Name of the company being evaluated.2. no – Identification number of the company.3. Company_n – Alternative identification of the company (possibly categorization).4. Data – Date of opinion issuance.5. old_num – Number of days that have passed since the opinion was issued.6. months_num – Number of months that have passed since the opinion was issued.7. BIG4_d – Binary variable (0/1) indicating whether the company is part of the Big Four.8. cathegory – Classification of the opinion issuer. The categories include:· practitioner – The opinion was issued by a practitioner.· expert – The opinion was issued by an expert.· other – The opinion was issued by someone categorized as "other."· researcher – The opinion was issued by a researcher.· teacher – The opinion was issued by an academic or educator.Opinion Issuer Characteristics:9. practitioner_d – Binary variable (0/1) indicating whether the opinion issuer is a practitioner.10. expert_d – Binary variable (0/1) indicating whether the opinion issuer is an expert.11. other_d / researcher_d / teacher_d – Binary variables (0/1) indicating whether the opinion issuer falls into one of these categories.Variables Related to Identified Problems:From here onward, the variables indicate whether the analyzed opinion highlights a specific problem. Each is coded as “1” if the problem is mentioned in the opinion, otherwise “0.” These align with the eight identified IFRS 17-related challenges:12. cohorts – Whether the opinion discusses problems related to annual cohorts, which may cause unnecessary complexity in financial reporting.13. contract_liabilities – Whether the opinion mentions problems with contract liabilities, which may include recognition, measurement, or classification issues.14. non-financial – Whether the opinion discusses risk adjustment for non-financial risk, which affects the measurement of insurance contracts.15. First-time – Whether the opinion mentions challenges related to first-time implementation, including the need for additional provisions and adjustments.16. IFRS 9 – Whether the opinion addresses interactions between IFRS 9 and IFRS 17, particularly how the classification of financial assets affects insurance contract accounting.17. rates – Whether the opinion discusses problems with the two methods for discount rate calculation, affecting the valuation of insurance liabilities.18. PAA – Whether the opinion refers to difficulties with the Premium Allocation Approach (PAA), an alternative method for measuring liabilities under IFRS 17.19. onerous – Whether the opinion highlights issues related to the treatment of onerous contracts, i.e., contracts expected to be loss-making, requiring special accounting treatment.20. understanding – Whether the opinion raises concerns about the complexity and understanding of IFRS 17, especially regarding its interpretation and practical application.21. systems – Whether the opinion highlights issues with IT systems, such as challenges in adapting accounting systems to IFRS 17 requirements.22. comparability – Whether the opinion mentions comparability issues, indicating concerns that IFRS 17 may reduce the consistency of financial reporting across companies.

The industry has grown over the five years to 2024 due to the growth of global demand for insurance products. The industry provides essential risk management services to downstream consumers and is a vital part of the financial sector, particularly concerning the industry's massive asset holdings. Industry operators protect individuals from current, immediate and long-term illness, injury and death costs. By merging various risks, life and health insurers protect a fraction of the potential loss. The role of life and health insurers has become increasingly important as the global population has aged. Although the industry provides essential products and services, operators are highly susceptible to macroeconomic shocks. Industry revenue is expected to grow at a CAGR of 0.6% to $5.5 trillion over the five years to 2024, including a decrease of 0.3% in 2024 alone. In addition to premiums from insurance underwriting, operators also obtain revenue from financial instruments, such as stocks and bonds, which generate income and capital gains. However, this exposure to financial markets, particularly for life insurers, means that revenue and profit can exhibit significant volatility. The decline in global interest rates has been the primary obstacle to the industry's expansion. Nevertheless, given the immediacy of health concerns, health insurance largely tempers revenue fluctuations for the industry. Market conditions are expected to recover moving forward. Thus, revenue is expected to increase at a CAGR of 0.9% to $5.8 trillion over the five years to 2029. Moreover, increasing employment levels globally are expected to drive demand for insurance. Meanwhile, demand for insurance is growing in emerging markets. As the wealth of these regions continues to grow, individuals will likely become more interested in ensuring their wealth and income against a range of risks. Additionally, the threat of volatile financial markets is anticipated to persist during the period and could hurt investment income, particularly if interest rates are forced to remain low.