The Digital Flood Insurance Rate Map (DFIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The DFIRM Database is derived from Flood Insurance Studies (FISs), previously published Flood Insurance Rate Maps (FIRMs), flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). The file is georeferenced to earth's surface using the UTM projection and coordinate system. The specifications for the horizontal control of DFIRM data files are consistent with those required for mapping at a scale of 1:24,000.

Abstract

Taiwan launched a single-payer National Health Insurance program on March 1, 1995.

Documentation

Taiwan launched a single-payer National Health Insurance program on March 1, 1995. As of 2014, 99.9% of Taiwan\342\200\231s population were enrolled. Foreigners in Taiwan are also eligible for this program. The database of this program contains registration files and original claim data for reimbursement. Large computerized databases derived from this system by the National Health Insurance Administration (the former Bureau of National Health Insurance, BNHI), Ministry of Health and Welfare (the former Department of Health, DOH), Taiwan and maintained by the National Health Research Institutes, Taiwan, are provided to scientists in Taiwan for research purposes.

An article describing these data in greater detail can be found here: Lessons From the Taiwan National Health Insurance Research Database

Patient characteristics Individuals enrolled in the Taiwanese national healthcare system

Data overview Data categories Inpatient Outpatient Pharmacy data Over-the-counter drugs Chinese medicine Clinician information Hospital information

Linkages include Household Birth certificate Death certificate Cancer Immunization record Reportable infectious disease

Notes If you are interested in a collaboration working with these data, please contact the Dr Ann Hsing at .

United States Property & Casualty Insurance: Net Underwriting Gain (Loss ) data was reported at 24.989 USD bn in Dec 2024. This records an increase from the previous number of 6.184 USD bn for Sep 2024. United States Property & Casualty Insurance: Net Underwriting Gain (Loss ) data is updated quarterly, averaging 4.567 USD bn from Mar 2012 (Median) to Dec 2024, with 52 observations. The data reached an all-time high of 24.989 USD bn in Dec 2024 and a record low of -30.037 USD bn in Sep 2023. United States Property & Casualty Insurance: Net Underwriting Gain (Loss ) data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG012: Property & Casualty Insurance: Industry Financial Snapshots.

Comprehensive dataset of 293 Insurance companies in Connecticut, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 243 Insurance companies in Iowa, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 351 Insurance companies in Kentucky, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

These Unemployment Insurance (UI) Data are produced from state-reported data contained in the Unemployment Insurance Data Base (UIDB) as well as UI-related data from outside sources (e.g., Bureau of Labor Statistics data on employment and unemployment and U.S. Department of Treasury data on state UI trust fund activities). These represent one way to research and track the employment status of those employed in the arts.

Indonesia Insurance Statistics: Number of Registered Insurers: Life Insurers data was reported at 57.000 Unit in 2023. This records a decrease from the previous number of 59.000 Unit for 2022. Indonesia Insurance Statistics: Number of Registered Insurers: Life Insurers data is updated yearly, averaging 55.000 Unit from Dec 2003 (Median) to 2023, with 21 observations. The data reached an all-time high of 61.000 Unit in 2017 and a record low of 45.000 Unit in 2011. Indonesia Insurance Statistics: Number of Registered Insurers: Life Insurers data remains active status in CEIC and is reported by Indonesia Financial Services Authority. The data is categorized under Indonesia Premium Database’s Insurance Sector – Table ID.RGA001: Insurance Statistics: Key Indicators.

The McGRAW Life Insurance Data and Lead database is a comprehensive and invaluable resource for accessing individuals actively searching for life insurance. This data is perfect for businesses looking to enhance their direct mail and email campaigns with high-quality, targeted leads.

Why Choose McGRAW Life Insurance Data?

In the competitive life insurance industry, the quality of your leads can make all the difference. McGRAW provides the most accurate and meticulously curated life insurance leads available. Our database includes information on 16 million individuals, both aged and in real-time, ensuring you can connect with prospects at various stages of their life insurance journey.

Features and Benefits:

1. Timely Inquiries:

   • 30, 60, 90-day aged leads: Reach out to individuals who have recently inquired about life insurance.
   • Up to 12 months: Access data on prospects who have shown interest in the past year.

2. High-Quality Leads:

   • Our leads are more than just names and contact numbers; they represent individuals actively seeking life insurance solutions. This means you can eliminate the guesswork and focus your resources on converting qualified leads into loyal customers.

3. Opt-ins specifically for final expense

4. High-intent consumers ready to speak in real time

5. Long-form, form-filled (10+ fields)

6. CPAs lower than industry average

7. National geographic coverage

8. API posting preferred, with same-week setup

9. Multi-level compliance

10 Proven campaign tactics for telemarketing, texting, and emailing

Our database is built on inquiries and quotes gathered over the past 30, 60, 90 days, and up to 12 months. This ensures that you are targeting individuals who are actively searching for life insurance, providing a valuable resource for your marketing strategies.

By partnering with McGRAW, you can strategically target your marketing efforts and achieve unparalleled results. Our life insurance leads enable you to connect with prospects who are already interested in life insurance products, making your campaigns more effective and efficient.

Comprehensive dataset of 966 Insurance companies in Georgia, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 1,917 Insurance companies in Argentina as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

The Flood Insurance Rate Map (FIRM) Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by the Federal Emergency Management Agency (FEMA). This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Datum of 1983.

Comprehensive dataset of 113 Insurance companies in West Virginia, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Data and code for the article Behavioral Economics and Auto Insurance: The Role of Biases and Heuristics". This paper analyzes how framing, anchoring and certainty effects may affect the behavior of the consumer of auto insurance. An experiment was carried out, with the face-to-face application of six versions of a questionnaire with 14 questions, for 163 respondents from an educational institution. Questions were prepared to analyze the existence of the Framing Effect, the Anchoring Effect and the Certainty Effect, in addition to the Deductible Effect (present in several insurance products). The theoretical framework of the paper is the Behavioral Economics. Data includes: Original answers, collected in the experiment Stata code used in the econometric procedure

Insurance: Loss Ratio: Voyage data was reported at 0.710 % in Feb 2025. This records a decrease from the previous number of 2.090 % for Dec 2024. Insurance: Loss Ratio: Voyage data is updated monthly, averaging 0.480 % from Jan 2011 (Median) to Feb 2025, with 167 observations. The data reached an all-time high of 3.080 % in Dec 2020 and a record low of -0.590 % in Mar 2011. Insurance: Loss Ratio: Voyage data remains active status in CEIC and is reported by Superintendence of Private Insurance. The data is categorized under Brazil Premium Database’s Insurance Sector – Table BR.RGD001: Insurance Loss Ratio.

United States Life Insurance: In Force: Number of Policies: Group data was reported at 118,000.000 Unit th in 2023. This records an increase from the previous number of 114,000.000 Unit th for 2022. United States Life Insurance: In Force: Number of Policies: Group data is updated yearly, averaging 119,000.000 Unit th from Dec 1920 (Median) to 2023, with 48 observations. The data reached an all-time high of 180,000.000 Unit th in 2007 and a record low of 2,000.000 Unit th in 1920. United States Life Insurance: In Force: Number of Policies: Group data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG008: Life Insurance: In Force.

United States Health Insurance: Premium Per Member Per Month data was reported at 364.000 USD in Sep 2024. This stayed constant from the previous number of 364.000 USD for Jun 2024. United States Health Insurance: Premium Per Member Per Month data is updated quarterly, averaging 262.000 USD from Mar 2012 (Median) to Sep 2024, with 51 observations. The data reached an all-time high of 364.000 USD in Sep 2024 and a record low of 178.000 USD in Sep 2013. United States Health Insurance: Premium Per Member Per Month data remains active status in CEIC and is reported by National Association of Insurance Commissioners. The data is categorized under Global Database’s United States – Table US.RG017: Health Insurance: Industry Financial Snapshots.

Comprehensive dataset of 23,341 Insurance brokers in United States as of June, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

Comprehensive dataset of 670 Insurance brokers in Arizona, United States as of July, 2025. Includes verified contact information (email, phone), geocoded addresses, customer ratings, reviews, business categories, and operational details. Perfect for market research, lead generation, competitive analysis, and business intelligence. Download a complimentary sample to evaluate data quality and completeness.

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