European insurance companies are more advanced with implementing digital enhancements to maintain resilience over the next **** months, according to a 2020 survey. ** percent of respondents in Europe were already implementing their digital transformation plans - slightly more than in North America, and significantly more than in the Asia Pacific region.

Comprehensive dataset containing 26,528 verified Insurance company businesses in United States with complete contact information, ratings, reviews, and location data.

NY Insurance Policy Assets, Liabilities, and Premiums Annually

Investigating the Impact of Financial Health on Health Insurance Costs

By State of New York [source]

About this dataset

This dataset tracks health insurance premiums written in New York annually since 2004. It provides vital insight into the amount of money and risk taken on by insurance companies in the state: including what types of insurers are writing policies, how much they are taking on in assets and liabilities, and how this has shifted over time. This data will be invaluable to those looking to understand large scale trends in terms of the health insurance industry. The data has been updated as recently as 2021, so it provides a comprehensive picture of changes year-over-year spanning nearly two decades

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How to use the dataset

This dataset contains vital information regarding health insurance premiums, assets and liabilities related to policies written in New York annually. It is designed to provide key insights into the performance of insurance companies in New York state.

The data consists of Type of Insurer, Company Name, Year, Assets, Liabilities and Premium Written for each policy written in every year since 2009. This data can be used to gain greater insight into the performance of certain companies within this industry over time as well as creating benchmarked comparison metrics against other companies within this market space.

For individual or team exploration projects – you may want to compare one company’s yearly assets/liabilities or premiums against the average value for that same period in order to identify high or low performing periods or take a look at how some variables changed across a 5 year (or wider) timescale e.g compare how did assets/liabilites changed over the duration of 5 years?

By utilizing basic data visualizations like scatterplots and bar graphs we can start gaining more insights from our analysis by looking at potential correlations between variables such as: Are premium prices related to their assets? Does company size have an impact on the premium price? Have liabilities remained constant compared with past years?

Administrators in management roles could also use this dataset to track yearly changes within their own companys results- such as tracking existing trends over longer periods with pay attention for changes which require further investigation/ research as necessary .

All in all this data set is a great tool for students , researchers & analysts alike!

Research Ideas

• Establishing a baseline of average health insurance premiums in New York by year across different insurers.
• Comparing insurance company assets and liabilities with their premium-written to provide an understanding of how profitable they are in the New York market.
• Tracking the growth and success of health insurers in the New York over time to understand changes in industry trends or policy standards

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

See the dataset description for more information.

Columns

File: health-insurance-premiums-on-policies-written-in-new-york-annually-1.csv | Column name | Description | |:--------------------|:--------------------------------------------------------------------------------------------------------------------------------| | Type of Insurer | This column indicates the type of insurer that wrote the policy. (String) | | Company Name | This column indicates the name of the company that wrote the policy. (String) | | Year | This column indicates the year that the policy was written in. (Integer) | | Assets | This column indicates the total assets of the company that wrote the policy. (Integer) | | Liabilities | This column indicates the total liabilities of the company that wrote the policy. (Integer) | | Premium Written | This column indicates the total amount paid by an individual or organization for a given product or service annually. (Integer) |

Acknowledgements

If you use this dataset in your research, please credit the original authors. If you use this dataset in your research, please credit State of New York.

Insurance industry and its branch institution statistics table (monthly report)

Kazakhstan Insurance Market: Number of Insurance Company: Life Insurance data was reported at 7.000 Unit in Aug 2018. This stayed constant from the previous number of 7.000 Unit for Jul 2018. Kazakhstan Insurance Market: Number of Insurance Company: Life Insurance data is updated monthly, averaging 7.000 Unit from Jan 2002 (Median) to Aug 2018, with 200 observations. The data reached an all-time high of 8.000 Unit in Jun 2015 and a record low of 1.000 Unit in Nov 2004. Kazakhstan Insurance Market: Number of Insurance Company: Life Insurance data remains active status in CEIC and is reported by Committee for Control and Supervision of the Financial Market and Financial Organizations. The data is categorized under Global Database’s Kazakhstan – Table KZ.Z009: Insurance Market Statistics.

Insurance Big Data Analytics Market Outlook

The global insurance big data analytics market size was valued at approximately $7.5 billion in 2023 and is expected to reach $25.4 billion by 2032, growing at a compound annual growth rate (CAGR) of 14.7% during the forecast period. The rapid growth of this market is primarily driven by the increasing volume of data generated by insurance companies and the necessity for data-driven decision-making processes. Advances in technology, such as artificial intelligence and machine learning, also play a pivotal role in the adoption of big data analytics within the insurance sector.

One of the main growth factors driving the insurance big data analytics market is the escalating demand for risk management solutions. Insurance companies are increasingly turning to big data analytics to better understand and predict risk, which in turn helps in designing more accurate insurance products. This capability is especially crucial in a world where risks are becoming increasingly complex and interconnected. Big data analytics allows insurers to gain deeper insights into customer behavior, market trends, and potential threats, thereby enabling them to make more informed decisions.

Customer analytics is another significant driver for this market. By leveraging big data analytics, insurance companies can provide more personalized services to their clients. Understanding customer needs and preferences allows insurers to tailor their products and services, improving customer satisfaction and retention rates. Additionally, big data analytics enables insurers to develop targeted marketing campaigns, helping them to attract and retain profitable customer segments. This ability to provide customized and relevant offerings significantly enhances the customer experience and loyalty, further fueling market growth.

The ability to detect and prevent fraud is a crucial aspect that promotes the adoption of big data analytics in the insurance industry. Instances of insurance fraud are on the rise, costing the industry billions of dollars annually. Big data analytics tools can sift through vast amounts of data to identify unusual patterns and detect fraudulent activities in real-time. This not only helps in minimizing financial losses but also ensures compliance with regulatory requirements. Consequently, the increasing focus on fraud detection and prevention is expected to drive the adoption of big data analytics solutions among insurers.

From a regional perspective, North America holds the largest market share in the insurance big data analytics market. This dominance can be attributed to the high adoption of advanced technologies and the presence of major insurance firms in the region. Additionally, stringent regulatory requirements pertaining to data management and reporting further propel the demand for big data analytics solutions. Europe follows closely, with significant investments in digital transformation initiatives within the insurance sector. Meanwhile, the Asia Pacific region is expected to witness the highest growth rate due to the burgeoning insurance market and increasing digitalization efforts in emerging economies such as China and India.

Component Analysis

The component segment of the insurance big data analytics market is divided into software and services. The software segment is anticipated to hold the largest market share during the forecast period. This is primarily due to the increasing need for robust data analytics tools that can manage and analyze the large volumes of data generated by insurance companies. Software solutions often include data management platforms, predictive analytics, and visualization tools that help insurers gain actionable insights. The continuous evolution of these software solutions, driven by advancements in artificial intelligence and machine learning, further enhances their capability to provide accurate and timely insights.

On the other hand, the services segment is also expected to witness significant growth. Services include consulting, implementation, and maintenance support, which are crucial for the successful deployment and operation of big data analytics solutions. Consulting services help insurers identify the right analytics solutions that align with their business objectives. Implementation services ensure the seamless integration of these solutions within the existing IT infrastructure, while maintenance support ensures their optimal performance over time. The growing complexity of big data analytics solutions necessitates the need for specialized services, driving the demand in this segm

The value of assets of insurance companies worldwide increased year-on-year from 2002 to 2021, except in 2008 and 2022 when a slight decrease was observed. In 2022, the assets of insurance companies globally amounted to approximately 35.7 trillion U.S. dollars - a decrease of almost five trillion U.S. dollars from the previous year. Overall, the value of assets of global insurance companies has grown by around 20 trillion U.S. dollars since 2002.

This data set includes a row for each type of non-appointment relationship between an insurance agent, agency, adjuster, and businesses and an insurance company or another person or business approved to manage insurance-related products or claims. To view a list of formal designations, or appointments, for agents to represent a regulated company, go to Active insurance company appointments for agents and adjusters. To view a list of formal designations, or appointments, for agencies to represent a regulated company, go to Active insurance company appointments for agencies and businesses.

Listing of consumer complaints filed against Insurance companies licensed in Connecticut. This dataset includes the Company, Line of Business, nature of complaint, outcome or resolution, and recovery.

Vietnam Number of Insurance Company: Life data was reported at 18.000 Unit in 2017. This stayed constant from the previous number of 18.000 Unit for 2016. Vietnam Number of Insurance Company: Life data is updated yearly, averaging 11.000 Unit from Dec 1999 (Median) to 2017, with 17 observations. The data reached an all-time high of 18.000 Unit in 2017 and a record low of 3.000 Unit in 1999. Vietnam Number of Insurance Company: Life data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under Global Database’s Vietnam – Table VN.Z003: Insurance Statistics.

ISO is an independent advisory organization that collects information on a community's building-code adoption and enforcement services in order to provide a ranking for insurance companies. ISO assigns a Building Code Effectiveness Classification from 1 to 10 based on the data collected. Class 1 represents exemplary commitment to building-code enforcement.Municipalities with better rankings are lower risk, and their residents' insurance rates can reflect that. The prospect of minimizing catastrophe-related damage and ultimately lowering insurance costs gives communities an incentive to enforce their building codes rigorously.This page provides data for the Insurance Services Organization (ISO) performance measure. This data includes residential and commercial building code enforcement ratings for the City of Tempe.The performance measure dashboard is available at 1.15 Insurance Services Organization (ISO) RatingAdditional InformationSource: Insurance Service Organization RatingContact: Chris ThompsonContact E-Mail: Christopher_Thompson@tempe.govData Source Type: ExcelPreparation Method: Information added to Excel spreadsheet from rating reportPublish Frequency: Every 5 YearsPublish Method: ManualData Dictionary

Comprehensive dataset containing 19 verified Insurance agency businesses in EH with complete contact information, ratings, reviews, and location data.

Life Insurance Premiums: First Year: General Insurance: Industry data was reported at 425.092 THB mn in Sep 2018. This records an increase from the previous number of 284.877 THB mn for Jun 2018. Life Insurance Premiums: First Year: General Insurance: Industry data is updated quarterly, averaging 304.219 THB mn from Mar 2016 (Median) to Sep 2018, with 11 observations. The data reached an all-time high of 650.465 THB mn in Dec 2017 and a record low of 121.086 THB mn in Mar 2016. Life Insurance Premiums: First Year: General Insurance: Industry data remains active status in CEIC and is reported by Office of Insurance Commission. The data is categorized under Global Database’s Thailand – Table TH.Z030: Life Insurance Statistics.

Life Insurance Industry Total Assets Statistics (Life Insurance Association of the Republic of China)

UnitedHealth was to be the largest insurer globally as of February 2025, with market capitalization amounting to approximately ***** billion U.S. dollars. UnitedHealth Group is a healthcare and insurance company headquartered in Minnesota. Global insurance industry - additional information Insurance is a form of risk management, where a person, called the insured or policyholder, signs a contract with a company, which is called an insurer or insurance carrier, in order to protect themselves from sudden losses. The contract between the two parties, called an insurance policy, states the circumstances and conditions under which the insured will be compensated. The major types of insurance are: life/health insurance and property/casualty insurance. The amount of money charged by an insurance company for active coverage is called an insurance premium and is most often paid in monthly installments. In 2022, the value of gross premiums generated by the global insurance industry amounted to more than *** trillion U.S. dollars. The United States was the ******* country in the insurance market in terms of value of life and non-life direct premiums written, with premiums estimated at **** trillion U.S. dollars for 2022. When ranking global insurers by their total assets, the Chinese insurance company Ping An Insurance placed first, with assets worth approximately *** trillion U.S. dollars. Ping An Insurance was also the company with the strongest brand value among insurance companies in 2023.

Vietnam Number of Insurance Company: Non Life data was reported at 30.000 Unit in 2017. This stayed constant from the previous number of 30.000 Unit for 2016. Vietnam Number of Insurance Company: Non Life data is updated yearly, averaging 27.000 Unit from Dec 1993 (Median) to 2017, with 19 observations. The data reached an all-time high of 30.000 Unit in 2017 and a record low of 1.000 Unit in 1993. Vietnam Number of Insurance Company: Non Life data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under Global Database’s Vietnam – Table VN.Z003: Insurance Statistics.

Vietnam Insurance Companies: Total Assets data was reported at 316,300.000 VND bn in 2017. This records an increase from the previous number of 248,247.000 VND bn for 2016. Vietnam Insurance Companies: Total Assets data is updated yearly, averaging 71,831.000 VND bn from Dec 1993 (Median) to 2017, with 19 observations. The data reached an all-time high of 316,300.000 VND bn in 2017 and a record low of 673.000 VND bn in 1993. Vietnam Insurance Companies: Total Assets data remains active status in CEIC and is reported by Ministry of Finance. The data is categorized under Global Database’s Vietnam – Table VN.Z003: Insurance Statistics.

The Asia-Pacific Life and Non-Life Insurance Market is Segmented by Insurance Type (Life Insurance, Non-Life Insurance), Distribution Channel (Agency Force, Bancassurance, Brokers & IFAs, and More), Customer Segment (Retail / Mass Market, High-Net-Worth & Affluent, and More), and Region. The Market Forecasts are Provided in Value (USD).

Taiwan Number of Insurance Companies: Non Life: Domestic: Headquarters data was reported at 17.000 Unit in 2017. This stayed constant from the previous number of 17.000 Unit for 2016. Taiwan Number of Insurance Companies: Non Life: Domestic: Headquarters data is updated yearly, averaging 17.000 Unit from Dec 1995 (Median) to 2017, with 23 observations. The data reached an all-time high of 18.000 Unit in 2001 and a record low of 16.000 Unit in 2005. Taiwan Number of Insurance Companies: Non Life: Domestic: Headquarters data remains active status in CEIC and is reported by Taiwan Insurance Institute. The data is categorized under Global Database’s Taiwan – Table TW.Z032: Insurance Statistics: Number of Companies and Employees (Annual).

National Situation Statistics Data Sheet (Policy Research Center)