Insurance: Claim Incurred data was reported at 6,589.776 BRL mn in Feb 2025. This records a decrease from the previous number of 6,851.124 BRL mn for Jan 2025. Insurance: Claim Incurred data is updated monthly, averaging 4,074.157 BRL mn from Dec 2013 (Median) to Feb 2025, with 135 observations. The data reached an all-time high of 8,320.939 BRL mn in May 2024 and a record low of 2,525.717 BRL mn in Jun 2014. Insurance: Claim Incurred data remains active status in CEIC and is reported by Superintendence of Private Insurance. The data is categorized under Global Database’s Brazil – Table BR.RG002: Insurance: Claims. [COVID-19-IMPACT]

The dataset is eligible in exploring Health Insurance fraud Claims using machine learning algorithms. Its well suited for students developimg ML models to predict Healthcare insurance claims fraud.

This file contains ultimate claims data taken from the private motor National Claims Iinformation Database (NCID). The claims are grouped together by accident year, the year in which the accident occurred. Not all claims are paid in the lifetime of the policy. Some claims, injury claims in particular, can take many years to be settled and be fully paid. Insurers estimate the cost/number of claims expected for a particular accident year, and this known as the ultimate cost/number of claims. The ultimate cost/number of claims is recalculated regularly, based on the most up-to-date information available. The more time that has passed since the accident year, the more certain the ultimate cost of claims becomes. To view the detailed NCID report kindly refer to the centralbank publication link in the Landing Page section under Additional Info.

SD, Standard deviation; NE, Northeast; NC, North Centrala Mean monthly percentage of population with medical encounters in the 3-months priorBeneficiary Baseline Characteristics By Study Period.

United States Health Insurance: Claims Per Member Per Month: Medicare data was reported at 1,111.000 USD in 2023. This records an increase from the previous number of 1,012.000 USD for 2022. United States Health Insurance: Claims Per Member Per Month: Medicare data is updated yearly, averaging 791.000 USD from Dec 2007 (Median) to 2023, with 17 observations. The data reached an all-time high of 1,111.000 USD in 2023 and a record low of 746.230 USD in 2007. United States Health Insurance: Claims Per Member Per Month: Medicare 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.RG022: Health Insurance: Operations by Lines of Business.

The Pharmaceuticals and Medical Devices Agency (PMDA) has conducted many pharmacoepidemiological studies for postmarketing drug safety assessments based on real-world data from medical information databases. One of these databases is the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB), containing health insurance claims of almost all Japanese individuals (over 100 million) since April 2009. This article describes the PMDA’s regulatory experiences in utilizing the NDB for postmarketing drug safety assessment, especially focusing on the recent cases of use of the NDB to examine the practical utilization and safety signal of a drug. The studies helped support regulatory decision-making for postmarketing drug safety, such as considering a revision of prescribing information of a drug, confirming the appropriateness of safety measures, and checking safety signals in real-world situations. Different characteristics between the NDB and the MID-NET® (another database in Japan) were also discussed for appropriate selection of data source for drug safety assessment. Accumulated experiences of pharmacoepidemiological studies based on real-world data for postmarketing drug safety assessment will contribute to evolving regulatory decision-making based on real-world data in Japan.

Problem Statement

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An insurance company faced significant inefficiencies in its claims processing operations. The manual review and assessment of claims were time-consuming, prone to errors, and resulted in delays that frustrated customers. The company needed a solution to streamline claims processing, reduce operational costs, and improve customer satisfaction.

Challenge

Automating insurance claims processing involved addressing several challenges:

Handling diverse claim types, including structured and unstructured data such as invoices, photographs, and customer narratives.

Ensuring accurate claims assessment while detecting potential fraud.

Integrating automation with existing systems without disrupting ongoing operations.

Solution Provided

An AI-powered claims processing system was developed using machine learning and workflow automation technologies. The solution was designed to:

Extract and validate data from claim submissions automatically.

Assess claims using predictive models to estimate coverage and liability.

Flag potential fraudulent claims for further investigation.

Development Steps

Data Collection

Collected historical claims data, including structured data from forms and unstructured data such as photos and handwritten notes, to train machine learning models.

Preprocessing

Standardized and cleaned data, ensuring compatibility across various sources. Applied optical character recognition (OCR) for extracting data from scanned documents.

Model Development

Developed machine learning models to evaluate claims based on historical trends and patterns. Built fraud detection algorithms to identify anomalies in claims data.

Validation

Tested the system with live claims data to ensure accuracy in assessment, fraud detection, and operational efficiency.

Deployment

Implemented the solution across the company’s claims processing system, enabling seamless operation and real-time processing.

Continuous Monitoring & Improvement

Established a feedback loop to refine models and workflows based on new data and user feedback.

Results

Accelerated Claims Processing Time

The automation system reduced claims processing time by 60%, enabling quicker payouts and enhancing customer satisfaction.

Reduced Operational Costs

Automating routine tasks lowered operational costs by minimizing manual labor and administrative overhead.

Improved Customer Satisfaction

Faster and more accurate claims processing improved customer experience and strengthened trust in the company’s services.

Enhanced Fraud Detection

The system’s predictive algorithms flagged suspicious claims effectively, reducing the risk of fraudulent payouts.

Scalable and Adaptive Solution

The solution scaled seamlessly to handle increased claim volumes, ensuring consistent performance during peak periods.

United States Health Insurance: Accident and Health: Net Incurred Claims data was reported at 1,094.702 USD bn in 2023. This records an increase from the previous number of 994.634 USD bn for 2022. United States Health Insurance: Accident and Health: Net Incurred Claims data is updated yearly, averaging 805.750 USD bn from Dec 2015 (Median) to 2023, with 9 observations. The data reached an all-time high of 1,094.702 USD bn in 2023 and a record low of 640.025 USD bn in 2015. United States Health Insurance: Accident and Health: Net Incurred Claims 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.RG020: Health Insurance: Accident and Health: Net Incurred Claims by Lines of Business.

This dataset reports total weekly unemployment insurance initial claims and continued weeks claimed statewide in Iowa by week. Data for the most current week is preliminary and will be revised the following week. Initial claims data for states are combined and published weekly by the U.S. Department of Labor, Employment and Training Administration. This national data is widely reported as an economic indicator. This data is based on the ETA-539 report. This dataset is based on administrative data. Claims activity represents the week the claims were processed. It may not always represent the week unemployment occurred.

The data set contains the insurance company wise number of Life insurance claims settled. The information is as per the respective public disclosures of the insurance companies made on IRDAI portal.

This file contains ultimate claims data taken from the Employers’ Liability, Public Liability and Commercial Property data in the National Claims Information Database (NCID). To view the detailed NCID report kindly refer to the Central Bank publication link in the Landing Page section under Additional Info.

NE, Northeast; NC, North Central; TZD, Thiazolidinedionesa Includes alpha-glucosidase, meglitinide analogs, glucagon-like peptide-1 agonist, and dipeptidyl peptidase-4 inhibitorsb Based on medical encounters in the 3-months prior to index drug dateBaseline Characteristics of New Users of Oral Anti-Diabetic Agents by Study Period.

Analysis of ‘Auto Insurance Claims Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/buntyshah/auto-insurance-claims-data on 12 November 2021.

--- No further description of dataset provided by original source ---

--- Original source retains full ownership of the source dataset ---

WA-APCD - Washington All-Payer Claims Database

The WA-APCD is the state’s most complete source of health care eligibility, medical claims, pharmacy claims, and dental claims insurance data. It contains claims from more than 50 data suppliers, spanning commercial, Medicaid, and Medicare managed care. The WA-APCD has historical claims data for five years (2013-2017), with ongoing refreshes scheduled quarterly. Workers' compensation data from the Washington Department of Labor & Industries will be added in fall 2018.

Download the attachment for the data dictionary and more information about WA-APCD and the data.

The UI weekly claims data are used in current economic analysis of unemployment trends in the Nation, and in each State. Initial claims measure emerging unemployment and continued weeks claimed measure the number of persons claiming unemployment benefits.

The Agency for Healthcare Research and Quality (AHRQ) created SyH-DR from eligibility and claims files for Medicare, Medicaid, and commercial insurance plans in calendar year 2016. SyH-DR contains data from a nationally representative sample of insured individuals for the 2016 calendar year. SyH-DR uses synthetic data elements at the claim level to resemble the marginal distribution of the original data elements. SyH-DR person-level data elements are not synthetic, but identifying information is aggregated or masked.

This file contains settled claims data taken from the Employers’ Liability, Public Liability and Commercial Property data in the National Claims Information Database (NCID). To view the detailed NCID report kindly refer to the Central Bank publication link in the Landing Page section under Additional Info.

The monthly summary report is intended to provide the user with a quick overview of the status of the UI system at the national and state levels. This summary report contains monthly information on claims activities and on the number and amount of payments under State unemployment insurance laws. This data is used in budgetary and administrative planning, program evaluation, and reports to Congress and the public.

United States Health Insurance: Claims Per Member Per Month: Medicaid data was reported at 398.000 USD in 2023. This records an increase from the previous number of 375.000 USD for 2022. United States Health Insurance: Claims Per Member Per Month: Medicaid data is updated yearly, averaging 291.000 USD from Dec 2007 (Median) to 2023, with 17 observations. The data reached an all-time high of 398.000 USD in 2023 and a record low of 182.340 USD in 2007. United States Health Insurance: Claims Per Member Per Month: Medicaid 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.RG022: Health Insurance: Operations by Lines of Business.

United States Health Insurance: Accident and Health: Net Incurred Claims: Comprehensive: Individual data was reported at 85.005 USD bn in 2023. This records an increase from the previous number of 70.368 USD bn for 2022. United States Health Insurance: Accident and Health: Net Incurred Claims: Comprehensive: Individual data is updated yearly, averaging 60.222 USD bn from Dec 2015 (Median) to 2023, with 9 observations. The data reached an all-time high of 85.005 USD bn in 2023 and a record low of 55.128 USD bn in 2017. United States Health Insurance: Accident and Health: Net Incurred Claims: Comprehensive: Individual 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.RG020: Health Insurance: Accident and Health: Net Incurred Claims by Lines of Business.