Healthcare frauds represent fraud in health insurance, falsifying of claims or medical records, submission of claims for services not provided by medical practitioners, and medical providers administrating more expensive tests and equipment, among others. Fraud detection involves efficient use of data analytics and other related techniques for preventing and detecting healthcare fraud. It is anticipated that the global market accounted for a market value of USD 639.07 million in 2017 and is expected to register a CAGR of ~26.7% over the assessment period from 2018 to 2023.
The increasing number of fraudulent activities in the healthcare sector is a key factor driving the growth of the market. According to the European Healthcare Fraud & Corruption Network, from the year 2014 to 2015, nearly 4,819 episodes of fraud (an average of 402 cases per month) were reported to the health system in the UK. Moreover, the growing number of patients seeking healthcare insurance, rising pressure of fraud, waste, and abuse on the healthcare spending, and high returns on investments are some factors that are anticipated to boost the market growth over the forecast period. On the other hand, some factors such as the reluctance to adopt healthcare fraud analytics in the developing economies, time-consuming deployment, and the need for frequent upgrades in fraud detection software can hamper the growth of the market.
Some of the prominent players in the market are Optum, Verscend Technologies, International Business Machines Corporation (IBM), McKesson, Fair Isaac, SAS Institute, Northrop Grumman, HCL Technologies, Wipro, Conduent, CGI Group, DXC Technology, Scio Health Analytics, LexisNexis, and Pondera Solutions.
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The Global Healthcare Fraud Detection Market has been segmented into component, delivery model, type, application, end user, and region.
The global healthcare fraud detection market, by component, has been segmented into services and software. The services segment held the largest market share in 2017 on the basis of component. The market growth of this segment can be attributed to the rising demand for fraud analytics services. The software segment is expected to hold the highest CAGR over the forecast period owing to the growing development of advanced healthcare fraud detection software.
The Global Healthcare Fraud Detection Market, by delivery model, has been segmented into on-premise delivery models and on-demand delivery models.
The global market, by type, has been segmented into descriptive analytics, predictive analytics, and prescriptive analytics. The descriptive segment is anticipated to dominate the market by type as descriptive analytics forms the base for effective application of predictive or prescriptive analytics.
On the basis of application, the market has been segmented into insurance claims review and payment integrity. The insurance claims review segment has been segmented into post-payment review and prepayment review.
By end user, the market has been segmented into private insurance payers, government agencies, employers, and others.
On the regional basis, the Americas is expected to dominate the global healthcare fraud detection market due to the increasing fraud cases in the healthcare sector, a large number of people seeking health insurance, and presence of favorable government initiatives to combat healthcare frauds in the region. Europe is anticipated to account the second largest market share in the global healthcare fraud detection market owing to the rising number of healthcare fraud and corruption in the European region, increasing development of the IT (Information Technology) sector, and improving scenario to combat fraud in healthcare. Asia-Pacific is anticipated to be the fastest growing region in the market due to continuously developing economies and high incidence rates of healthcare frauds in the region. Furthermore, the Middle East and Africa has the least share of the market. In this region, the Middle East is likely to hold a major share owing to the rising occurrences of health insurance frauds.
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Table Of Contents:
Chapter 1. Report Prologue
Chapter 2. Market Introduction
2.2 Scope of the Study
2.2.1 Research Objective
Chapter 3. Research Methodology
3.2 Primary Research
3.3 Secondary Research
3.4 Market Size Estimation
Chapter 4. Market Dynamics
4.5 Macroeconomic Indicators
4.6 Technology Trends & Assessment
Chapter 5. Market Factor Analysis
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