Dataset

This dataset was created by Bunty Shah

Contents

1) Data Introduction • The Insurance Claim Dataset is a tabular dataset collected to predict whether an insurance claim will be made (yes/no) based on information such as the policyholder’s age, gender, BMI, average daily steps, number of children, smoking status, residential region, and medical charges billed by health insurance.

2) Data Utilization (1) Characteristics of the Insurance Claim Dataset: • The dataset integrates various factors such as health status, lifestyle habits, and demographic characteristics, making it suitable for practical use in insurance risk prediction and customer segmentation.

(2) Applications of the Insurance Claim Dataset: • Development of Insurance Claim Prediction Models: The dataset can be used to develop machine learning models that classify whether an insurance claim will be filed based on multiple input features. • Insurance Product Development and Risk Assessment: By analyzing the probability of claims for different customer profiles, the dataset can be used for product design, risk management, and premium pricing in practical policy planning.

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]

This service provides web services used to obtain claims-related data for patients. Users of this service are intended to be healthcare providers.

Explore Macgence’s USA Insurance Claim OCR dataset—high-quality annotated images to train and evaluate document automation AI systems.

Insurance Claim

## Overview

Insurance Claim is a dataset for object detection tasks - it contains Grass annotations for 286 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

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.

The dataset includes fiscal year data for initial claims for SSA disability benefits that were referred to a state agency for a disability determination. Specific data elements for each year and state include receipts, determinations, eligible population, and favorable determination rates.

The recent two years' statistics of property and casualty insurance claims rates - (annual) - by company (insurance development center)

Between 2016 and 2020, registration and/or eligibility was the main reason for **** percent of health insurance claims being denied in the United States. Furthermore, missing or invalid claim data caused over ** percent of health insurance claims to be denied in this time period. This statistic illustrates the leading reasons for denials of healthcare claims in the United States (U.S.) in 2020.

1) Data Introduction • The Vehicle Insurance Claim Fraud Detection Dataset is a tabular insurance fraud detection dataset that includes vehicle information, accident and insurance details, and claims details for vehicle insurance claims, and labels each claim as a fraudulent or not.

2) Data Utilization (1) Vehicle Insurance Claim Fraud Detection Dataset has characteristics that: • Each row contains a variety of variables, including vehicle attributes, models, accident details, insurance type and duration, and claim history, as well as the target variable, FraudFound_P. • The data are based on real insurance claim cases and are designed to be suitable for insurance fraud detection and classification model development. (2) Vehicle Insurance Claim Fraud Detection Dataset can be used to: • Development of Insurance Fraud Detection Models: You can build a machine learning-based insurance fraud classification and prediction model by leveraging various vehicle and accident and insurance attributes. • Analyzing fraud patterns and risk factors: You can use billing data and fraud to analyze fraud patterns, risk factors, insurance policy improvements, and more.

Claim is a provider issued list of professional services and products which have been provided or are to be provided, to a patient which is sent to an insurer for reimbursement.

Oregon workers' compensation claims counts. Where available, the data is provided since 1968, the year Oregon's modern workers' compensation system began. The data is presented in the Department of Consumer and Business Services report at https://www.oregon.gov/dcbs/reports/compensation/Pages/index.aspx. The attached pdf provides definitions of the data.

Content

This is "Sample Insurance Claim Prediction Dataset" which based on "[Medical Cost Personal Datasets][1]" to update sample value on top.

age : age of policyholder sex: gender of policy holder (female=0, male=1) bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height, objective index of body weight (kg / m ^ 2) using the ratio of height to weight, ideally 18.5 to 25 steps: average walking steps per day of policyholder children: number of children / dependents of policyholder smoker: smoking state of policyholder (non-smoke=0;smoker=1) region: the residential area of policyholder in the US (northeast=0, northwest=1, southeast=2, southwest=3) charges: individual medical costs billed by health insurance insuranceclaim: yes=1, no=0

Insurance Claim Services Market Outlook

According to our latest research, the global Insurance Claim Services market size reached USD 47.8 billion in 2024, propelled by the increasing demand for digital transformation and automation in the insurance sector. The market is expected to grow at a robust CAGR of 8.1% during the forecast period, reaching USD 89.5 billion by 2033. This growth is primarily driven by the surging adoption of advanced technologies such as artificial intelligence, machine learning, and cloud-based solutions, which are revolutionizing claims processing and enhancing customer experience. The market’s expansion is further supported by the rising incidence of insurance claims across property, health, auto, and life insurance segments, as insurers strive to optimize operations and minimize fraudulent activities.

One of the key growth factors for the Insurance Claim Services market is the increasing complexity and volume of insurance claims worldwide. As global economic activities intensify and consumer awareness regarding insurance coverage grows, more individuals and businesses are filing claims across various insurance products. This surge in claims is compelling insurers to invest in efficient claim management solutions that can automate workflows, reduce manual intervention, and accelerate settlement cycles. Moreover, the COVID-19 pandemic has highlighted the importance of robust insurance claim services, particularly in the health and life insurance sectors, where claim volumes have spiked. Insurers are now prioritizing seamless digital interfaces and automated claim validation to meet rising customer expectations and regulatory requirements.

Another significant driver is the integration of advanced analytics and artificial intelligence into insurance claim services. Modern claim management platforms leverage AI-driven tools for fraud detection, predictive analytics, and real-time risk assessment, enabling insurers to identify suspicious claims and mitigate losses effectively. The deployment of machine learning algorithms and natural language processing enhances the accuracy of claim adjudication, reduces processing time, and delivers personalized customer support. Insurtech startups and established players are investing heavily in R&D to develop innovative solutions that streamline claim handling, improve transparency, and reduce operational costs. This technological evolution is transforming the traditional insurance landscape and fostering market growth.

Furthermore, regulatory compliance and evolving customer expectations are shaping the Insurance Claim Services market. Governments and regulatory bodies across regions are implementing stringent guidelines to ensure fair claim settlements, transparency, and data security. Insurers are adopting digital claim services to comply with these regulations and provide customers with real-time claim tracking, digital documentation, and secure payment options. The growing emphasis on customer-centricity is prompting insurers to offer omnichannel claim services, including mobile apps, online portals, and virtual assistants, to enhance accessibility and satisfaction. As a result, the market is witnessing a shift from legacy systems to modern, cloud-based claim management platforms that offer scalability, agility, and improved data analytics capabilities.

From a regional perspective, North America continues to dominate the Insurance Claim Services market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of leading insurance companies, high digital adoption rates, and a mature regulatory environment contribute to North America’s leadership. Europe is experiencing steady growth, driven by increasing insurance penetration and technological advancements. Meanwhile, Asia Pacific is emerging as the fastest-growing region, fueled by rapid urbanization, rising disposable incomes, and expanding insurance coverage in countries such as China, India, and Japan. Latin America and the Middle East & Africa are also witnessing gradual adoption of digital claim services as insurers seek to enhance operational efficiency and customer engagement.

Service Type Analysis

The Insurance Claim Services market is segmented by service type into Property & Casualty Claims, Health Insurance Claims, Life Insurance Claims, Auto Insurance Claims, and Others. Property & Casualty Claims represent a significant portion of the market, driven by the increasing frequ

This data set contains DOT employee workers compensation claim data for current and past DOT employees. Types of data include claim data consisting of PII data (SSN, Name, Date of Birth, Home Address, Financial Institution, medical, etc.) and claim data from the Department of Labor

The Workers’ Compensation Board (WCB) administers and regulates workers’ compensation benefits, disability benefits, volunteer firefighters’ benefits, volunteer ambulance workers’ benefits, and volunteer civil defense workers’ benefits. The WCB processes and adjudicates claims for benefits; ensures employer compliance with the requirement to maintain appropriate insurance coverage; and regulates the various system stakeholders, including self-insured employers, medical providers, third party administrators, insurance carriers and legal representatives. Claim assembly occurs when the WCB learns of a workplace injury and assigns the claim a WCB claim number. The WCB “assembles” a claim in which an injured worker has lost more than one week of work, has a serious injury that may result in a permanent disability, is disputed by the carrier or employer, or receives a claim form from the injured worker (Form C-3). A reopened claim is one that has been reactivated to resolve new issues following a finding that no further action was necessary

As per Cognitive Market Research's latest published report, the Global Insurance Claims Management market size was $15,764.89 Million in 2024 and it is forecasted to reach $22,340.54 Million by 2030. Insurance Claims Management Industry's Compound Annual Growth Rate will be 6.09% from 2023 to 2030. Market Dynamics of the Insurance Claims Management Solution Market

Market Driver of the Insurance Claims Management Solution

Rising Demand for Faster and Error-Free Claims Processing: Insurers are adopting claims management solutions to reduce manual paperwork, minimize errors, and accelerate turnaround time. This automation improves customer satisfaction, reduces operational costs, and enhances competitive edge in an increasingly digital-first insurance ecosystem. Increasing Adoption of AI, Machine Learning, and Automation: Advanced technologies like AI and machine learning are transforming claims handling through intelligent fraud detection, predictive analytics, and automated decision-making. These features are driving adoption among insurers aiming to modernize legacy systems and streamline complex workflows. Growth of Health, Auto, and Property Insurance Segments: Expanding insurance coverage across sectors leads to a growing volume of claims. Scalable, cloud-based claims management platforms enable insurance firms to handle large claim inflows efficiently, especially in fast-growing health, vehicle, and disaster-related insurance categories.

Market Restraints of the Insurance Claims Management Solution Market

Increasing Demand for Swift and Accurate Claims Processing: Insurers are implementing claims management solutions to decrease manual documentation, lessen errors, and speed up turnaround times. This automation enhances customer satisfaction, lowers operational expenses, and strengthens competitive advantage in a progressively digital-centric insurance landscape. Rising Utilization of AI, Machine Learning, and Automation: Cutting-edge technologies such as AI and machine learning are revolutionizing claims processing through sophisticated fraud detection, predictive analytics, and automated decision-making. These capabilities are encouraging insurers to adopt modernized systems and simplify intricate workflows. Expansion of Health, Auto, and Property Insurance Sectors: The broadening of insurance coverage across various sectors results in an increasing number of claims. Scalable, cloud-based claims management systems allow insurance companies to manage substantial claim volumes effectively, particularly in rapidly expanding health, automotive, and disaster-related insurance segments.

Market Trends of the Insurance Claims Management Solution Market

Shift Toward Cloud-Based Claims Management Platforms: Cloud-based solutions provide scalability, cost-effectiveness, and remote accessibility, rendering them suitable for contemporary insurers. These platforms facilitate real-time data sharing, expedited updates, and smooth third-party integrations, prompting a shift from on-premise to cloud-native claims infrastructure. Integration of Customer Self-Service Portals and Mobile Apps: In order to improve transparency and minimize service delays, insurers are introducing mobile applications and portals that allow policyholders to submit claims, upload documents, and monitor claim status in real time. This movement enhances user experience while decreasing reliance on call centers. Emphasis on End-to-End Digital Transformation: Insurers are implementing comprehensive digital transformation strategies that encompass claims automation, CRM integration, chatbot assistance, and omnichannel communication. Claims management solutions are advancing into multifunctional platforms that provide support for analytics, compliance, fraud detection, and tailored customer engagement.

Opportunity for the Insurance Claims Management Solution Market

Predictive Maintenance for Claims Management is an opportunity for the market

The insurance claims management market has a new opportunity in leveraging predictive maintenance to improve claims management. Predictive maintenance enables insurers to anticipate and prevent potential claims, reducing losses and improving overall business performance. By leveraging predictive maintenance, insurers can develop more proactive claims management strategies, improving policyholder satisfaction and loyalty. By implementing predictive ma...

Accelerate claims processing thanks to Koncile's AI OCR: reliable extractions from PDFs or scans, with JSON, Excel or API export.

This resource provides the adjudication details from the processing of a Claim resource; it showcases the adjudicated response to a Claim, Predetermination or Preauthorization.