The Global Healthcare Fraud Analytics Market size was calculated at USD 1.5 Billion in 2021 and is projected to reach 5.0 Billion by 2027, growing at a CAGR 26.7% during the forecast period, 2021-2027. Market growth can be allocated a large number of fraudulent activities in healthcare, the increase in the number of patients looking for health insurance, gives high returns on investment, and the increasing number of pharmacy claims-related frauds. However, the insufficiency of skilled persons is expected to shortfall the growth of the health care fraud analytics market. However, the unskilled and un-professional personnel are expected to slow down the growth of this market. The global healthcare fraud analytic market is projected to be driven by the growing fraudulent activities in healthcare, the increased number of patients seeking health insurance, and the growth in the prepayment review models in the insurance policies.
Healthcare fraud occurs when a person, a group of people, or a company knowingly misrepresents the type, the scope, or the identification of the medical service provided in a manner that could result in unauthorized payments being made—for example- falsifying certificates of medical necessity and billing for services not medically necessary, falsifying plans of treatment or medical records to justify insurance claim, falsification charges or entitlements to payments in cost records. Beneficiaries and other healthcare recipients pay for these significant losses through higher premiums, increased taxes and reduced services. In recent years, fiscal intermediaries and carriers for Medicare have been required to send notices and descriptions of benefits to Medicare users and patients in virtually all circumstances. All beneficiaries must review and verify the information on these documents and question any entries or notations that are compatible with or unconnected to the essential health care services provided. In particular, you should be attentive to and question notices and explanations that memorialize payment for any medical services, medical treatment, supplies or equipment that you did not receive; duplicate payments for the same services or items or home medical equipment while you were hospitalized.
Healthcare fraud occurs when a person, a group of people, or a company knowingly misrepresents the type, the scope, or the identification of the medical service provided in a manner that could result in unauthorized payments being made—for example- falsifying certificates of medical necessity and billing for services not medically necessary, falsifying plans of treatment or medical records to justify insurance claim, falsification charges or entitlements to payments in cost records. Beneficiaries and other healthcare recipients pay for these significant losses through higher premiums, increased taxes and reduced services. In recent years, fiscal intermediaries and carriers for Medicare have been required to send notices and descriptions of benefits to Medicare users and patients in virtually all circumstances. All beneficiaries must review and verify the information on these documents and question any entries or notations that are compatible with or unconnected to the essential health care services provided. In particular, you should be attentive to and question notices and explanations that memorialize payment for any medical services, medical treatment, supplies or equipment that you did not receive; duplicate payments for the same services or items or home medical equipment while you were hospitalized.
The rise in disposable income created in the individual life, globally the healthcare expenditure is rising especially in the low and the middle earning countries. As per the World Health Organization (WHO) 2016 report, the rise in healthcare expenditure in these countries was approximately 6% per annum compared to 4% in high-income countries.
Before the Covid-19, the healthcare fraud analytics market grew proportionally with the individual’s income.
The global Healthcare Fraud Analytics market faces many challenges, temporary shutdown of business, and break from indoor/outdoor activities, travel bans and quarantines. Supply and demand fluctuations, stock market changes, falling business assurance, and many uncertainties negatively impact business dynamics. The healthcare industry has shown many fraud cases done by the patients, physicians’ doctors and other medical service providers. Many healthcare specialists and providers have been seen in fraudulent activities only for profit. In the healthcare sector, fraudulent actions done by patients include fraudulent sickness certificates, prescription fraud and unnecessary medical charges.
The Healthcare Fraud Analytics Market is estimated to increase steadily after the covid-19 breakout. One of the major elements driving the demand for the healthcare fraud analytic market is the increase in the popularity of healthcare communication through social media, rise in the number of health care BPO and fraud identity management software and government support and initiative in the healthcare and fraud marketing. Also, The rapid acceptance of cloud-based analytical solutions and the effectiveness of artificial intelligence in healthcare services and solutions.
The market is segmented on descriptive type, application type, delivery model type and end-user. Based on the solution type, the descriptive analytics segment is considered the highest share of the market in 2019. Descriptive analytics uses the basics of descriptive analytics and integrates them with additional data sources to produce meaningful insights
The healthcare fraud market is segmented into the on-premise and on-demand models. The on-demand models involve cloud-based and web-based models. The on-demand segment is calculated the highest CAGR during the forecast period. Factors such as on-demand self-serving analytical, the lack of up-front capital investment for hardware, extreme capacity flexibility, and the pay-as-you-go pricing model drive the demand for on-demand fraud detection solutions.
In 2020, the insurance claims review segment was considered the largest market share.
The healthcare fraud analytics market is segmented into insurance claims review, medical and pharmacy billing exploitation and misuse, payment honesty, and other applications. In 2019, the insurance claims review segment controlled the healthcare fraud analytics market. The rise in the number of patients looking for health insurance, the increase in the number of fraudulent claims, and the increase in acceptance of the prepayment review model are expected to drive this segment’s growth in coming years. The insurance claims review segment is mainly divided into post-payment, and prepayment review, with the latter, anticipated to register the highest growing share during the forecasts period. It is mainly because prepayment review protocols and analytics can help organizations proactively prevent fraud before payment, allowed to take rapid action. As a result, prepayment review solutions are assumed to gain more attention.
The global healthcare fraud analytics market has to be segmented into North America, Europe, APAC, South America and the Middle East and Africa. North America estimated the largest share in the healthcare fraud analytics market in 2019. The highest share of the North American market is allocated to the large number of people holding health insurance, growing healthcare fraud, favorable government anti-fraud initiatives, the pressure to reduce healthcare costs—technological advancements, and greater product and services availability in the region. Most leading healthcare fraud detection market players have their headquarters in North America.
The key player in the global health care analytical markets are IBM Corporation, Optum, INC., Cotiviti, INC., Change Healthcare, Fair Isaac Corporation, SAS Institute Inc., EXL Services Holdings, Wipro Limited, Conduent, Incorporated, CGI Inc, HCL Technologies Limited, Qlarant, DXC Technology, Northrop Grumman Corporation, LexisNexis, Healthcare Fraud Sheild, Sharecare, FraudLens, HMS Holding Corp., Codoxo, H20.ai, Pondera Solutions, Friss, Multiplan, FraudScope.
| Report Attribute | Details |
|---|---|
| Market Size Value in 2021 | USD 1.5 Billion |
| The revenue forecast in 2027 | USD 5 Billion |
| Growth Rate | CAGR of 26.7 % from 2020 to 2027 |
| Historical data | 2017-2019 |
| Forecast period | 2021 – 2027 |
| Region covered | North America, Europe, South America, Asia-Pacific, and Middle East & Africa |
| Key companies Profiled | IBM Corporation, Optum, INC., Cotiviti, INC., Change Healthcare, Fair Isaac Corporation, SAS Institute Inc., EXL Services Holdings, Wipro Limited, Conduent, Incorporated, CGI Inc, HCL Technologies Limited, Qlarant, DXC Technology, Northrop Grumman Corporation, LexisNexis, Healthcare Fraud |
By Solution Type
By Delivery Type
By Application Type
By End-users
By Region
The size of the Healthcare Fraud Analytic market, USD1.5 Billion in 2021, will reach USD5.0 Billion by 2027.
The growth rate of the global healthcare fraud analytic market is 26.7% during the forecast period.
The major driver for the growth of the healthcare fraud analytic market is: increase in the number of fraudulent activities, awareness of patients & service providers and government support and initiatives plans for insurance policies.
IBM Corporation, Optum, INC., Cotiviti, INC., Change Healthcare, Fair Isaac Corporation, SAS Institute Inc., EXL Services Holdings, Wipro Limited, Conduent, Incorporated, CGI Inc, HCL Technologies Limited, Qlarant, DXC Technology, Northrop Grumman Corporation, LexisNexis, Healthcare Fraud Sheild, Sharecare, FraudLens, HMS Holding Corp., Codoxo, H20.ai, Pondera Solutions, Friss, Multiplan, FraudScope.
North America region has dominated the global healthcare fraud analytics market because of the increasing cases of healthcare fraud and growing favorable government initiatives to combat healthcare fraud. However, an increasing number of healthcare payer organizations are opting for on-demand models for analytics due to their accessibility, flexibility, scalability and cost-effectiveness.
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