The global healthcare fraud detection Market was valued at $1,098.2 million in 2021, and is projected to reach $3,600.0 million by 2031, registering a CAGR of 12.6% from 2022 to 2031.
The goal of fraud detection is to stop someone from obtaining money or other items through deceptive means. Various industries, including medical and healthcare, use fraud detection techniques. healthcare fraud detection involves account audits and detective work. A thorough account audit might discover suspect policy holders and suppliers. It is ideal to carefully audit each and every claim one at a time. However, there are no realistic way to audit all claims. Fraud detection management is done by the techniques such as to look through millions of transactions, classify, organize, and segment data in order to locate patterns and identify fraud, data mining, estimation of the connections between independent and dependent variables. Data matching is a technique used to compare two collections of data, remove out duplicates, and establish connections between data.
Healthcare fraud, waste, and abuse are actually prevented by the healthcare fraud detection industry. Healthcare fraud is the deliberate distortion of facts by patients or healthcare personnel that results in unlawful payments or benefits. Examples of healthcare fraud include the filing of numerous claims by different providers for the same patients, the falsification of data by doctors, the submission of claims for services that have not been rendered, and the misrepresentation of dates for various treatments, frequency, duration, or service descriptions. The various activities involving fraud in medical industries has increased. Furthermore, the increased fraud cases, abuse of medical products and equipment and misuse of healthcare funds is projected to drive the market growth.
The major factor that drives the market growth of healthcare fraud detection in healthcare market is increase in number of patients seeking health insurance. The other factors such as increase in fraudulent cases, and misuse of funds offered by healthcare boost the growth of the healthcare fraud detection market. A small number of auditors must manually evaluate and pinpoint the dubious medical insurance claims to manually discover healthcare fraud.
However, more effective and automated methods of detecting healthcare frauds have been developed because to recent breakthroughs in machine learning and data mining techniques. In recent years, there has been an increase in interest in mining healthcare data for fraud detection also boosting the global healthcare fraud detection market. The breakthrough advances in machine learning and artificial intelligence, increased in data security concern in healthcare industry restraining the global healthcare fraud detection market.
The healthcare fraud detection market segmented on the basis of type, component, application, end user and region. By type, the market is segmented into descriptive analytics, predictive analytics and prescriptive analysis. By component the market is fragmented into service and software. By application the market divided into insurance claims review and payment integrity.
By end user, the market is segmented into healthcare payer, government agencies and others. The healthcare payer further segmented into public payer and private payer. The others segment includes employers, healthcare providers and third-party service providers. Region wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Major key players that operate in the global healthcare fraud detection market are International Business Machines Corporation (IBM), Optum, Verscend Technologies, McKesson Corporation, FAIR ISAAC Corporation, SAS Institute Inc., HCL Technologies, Wipro Limited, Conduent, CGI Group, DXC Technology Company, UnitedHealth Group, Exlservice Holdings Inc., Scio inspire Corp, LexisNexis, OSP Labs, Northrop Grumman.
The goal of fraud detection is to stop someone from obtaining money or other items through deceptive means. Various industries, including medical and healthcare, use fraud detection techniques. healthcare fraud detection involves account audits and detective work. A thorough account audit might discover suspect policy holders and suppliers. It is ideal to carefully audit each and every claim one at a time. However, there are no realistic way to audit all claims. Fraud detection management is done by the techniques such as to look through millions of transactions, classify, organize, and segment data in order to locate patterns and identify fraud, data mining, estimation of the connections between independent and dependent variables. Data matching is a technique used to compare two collections of data, remove out duplicates, and establish connections between data.
Healthcare fraud, waste, and abuse are actually prevented by the healthcare fraud detection industry. Healthcare fraud is the deliberate distortion of facts by patients or healthcare personnel that results in unlawful payments or benefits. Examples of healthcare fraud include the filing of numerous claims by different providers for the same patients, the falsification of data by doctors, the submission of claims for services that have not been rendered, and the misrepresentation of dates for various treatments, frequency, duration, or service descriptions. The various activities involving fraud in medical industries has increased. Furthermore, the increased fraud cases, abuse of medical products and equipment and misuse of healthcare funds is projected to drive the market growth.
The major factor that drives the market growth of healthcare fraud detection in healthcare market is increase in number of patients seeking health insurance. The other factors such as increase in fraudulent cases, and misuse of funds offered by healthcare boost the growth of the healthcare fraud detection market. A small number of auditors must manually evaluate and pinpoint the dubious medical insurance claims to manually discover healthcare fraud.
However, more effective and automated methods of detecting healthcare frauds have been developed because to recent breakthroughs in machine learning and data mining techniques. In recent years, there has been an increase in interest in mining healthcare data for fraud detection also boosting the global healthcare fraud detection market. The breakthrough advances in machine learning and artificial intelligence, increased in data security concern in healthcare industry restraining the global healthcare fraud detection market.
The healthcare fraud detection market segmented on the basis of type, component, application, end user and region. By type, the market is segmented into descriptive analytics, predictive analytics and prescriptive analysis. By component the market is fragmented into service and software. By application the market divided into insurance claims review and payment integrity.
By end user, the market is segmented into healthcare payer, government agencies and others. The healthcare payer further segmented into public payer and private payer. The others segment includes employers, healthcare providers and third-party service providers. Region wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Major key players that operate in the global healthcare fraud detection market are International Business Machines Corporation (IBM), Optum, Verscend Technologies, McKesson Corporation, FAIR ISAAC Corporation, SAS Institute Inc., HCL Technologies, Wipro Limited, Conduent, CGI Group, DXC Technology Company, UnitedHealth Group, Exlservice Holdings Inc., Scio inspire Corp, LexisNexis, OSP Labs, Northrop Grumman.
KEY BENEFITS FOR STAKEHOLDERS
- This report provides a quantitative analysis of the market segments, current trends, estimations, and dynamics of the healthcare fraud detectionmarket analysis from 2021 to 2031 to identify the prevailing healthcare fraud detection market opportunities.
- The market research is offered along with information related to key drivers, restraints, and opportunities.
- Porter's five forces analysis highlights the potency of buyers and suppliers to enable stakeholders make profit-oriented business decisions and strengthen their supplier-buyer network.
- In-depth analysis of the healthcare fraud detection market segmentation assists to determine the prevailing market opportunities.
- Major countries in each region are mapped according to their revenue contribution to the global market.
- Market player positioning facilitates benchmarking and provides a clear understanding of the present position of the market players.
- The report includes the analysis of the regional as well as global healthcare fraud detection market trends, key players, market segments, application areas, and market growth strategies.
Key Market Segments
By Application
- Insurance Claims Review
- Payment Integrity
By End User
- Healthcare Payer
- Type
- Public Payers
- Private players
- Government Agencies
- Others
By Type
- Descriptive Analytics
- Predictive Analytics
- Prescriptive Analysis
By Component
- Services
- Software
By Region
- North America
- U.S.
- Canada
- Mexico
- Europe
- Germany
- France
- UK
- Italy
- Spain
- Rest of Europe
- Asia-Pacific
- China
- Australia
- India
- South Korea
- Rest of Asia-Pacific
- Japan
- LAMEA
- Brazil
- Saudi Arabia
- South Africa
- Rest of LAMEA
Key Market Players
- International Business Machines Corporation (IBM)
- Optum Inc.
- Verscend Technologies
- McKesson Corporation
- FAIR ISAAC Corporation
- SAS Institute Inc.
- HCL Technologies
- WIPRO LIMITED
- Conduent
- CGI Group
- DXC Technology Company
- UnitedHealth Group, Inc.
- Exlservice Holdings Inc.
- Cotiviti Inc.
- LexisNexis
- OSP Labs
- Northrop Grumman
- Northrop Grumman Corp
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Table of Contents
CHAPTER 1: INTRODUCTION
CHAPTER 2: EXECUTIVE SUMMARY
CHAPTER 3: MARKET OVERVIEW
CHAPTER 4: HEALTHCARE FRAUD DETECTION MARKET, BY TYPE
CHAPTER 5: HEALTHCARE FRAUD DETECTION MARKET, BY COMPONENT
CHAPTER 6: HEALTHCARE FRAUD DETECTION MARKET, BY APPLICATION
CHAPTER 7: HEALTHCARE FRAUD DETECTION MARKET, BY END USER
CHAPTER 8: HEALTHCARE FRAUD DETECTION MARKET, BY REGION
CHAPTER 9: COMPANY LANDSCAPE
CHAPTER 10: COMPANY PROFILES
List of Tables
List of Figures
Executive Summary
According to the report, titled, “Healthcare Fraud Detection Market," the Healthcare fraud detection market was valued at $1.1 billion in 2021, and is estimated to reach $3.6 billion by 2031, growing at a CAGR of 12.6% from 2022 to 2031.The misrepresentation or making false statements about the medical bills, healthcare funds, or the nature of the medical treatment or service provided in a way that could lead to the payment of unlawful amounts, is considered as healthcare or medical fraud. Some cases of medical fraud are misleading the person providing the service, billing for services with inadequate documentation, falsifying the quality of service offered and submitting invoices for goods and services that have not been delivered. The fraud detection traditionally was done by the manual ways; however, this strategy becomes time-consuming and ineffective with a huge data collection. Progression in machine learning and data mining tools draw attention to automated fraud detection systems. Moreover, the global healthcare fraud detection market is expanding due to increased fraud in healthcare domain, increase in pressure of abuse and fraud, and rise in patient benefiting by health insurance. The segment descriptive analysis is a sort of data analysis that aids in accurately describing, displaying, or summarizing data points so that patterns may appear that satisfy all of the data's requirements.
Descriptive analysis segment is expanding as it offering various tools such as variance calculator, percentile calculator and scatter plot chart maker, with line of best fit. A subcategory of advanced analytics called predictive analytics uses historical data along with statistical modelling, data mining, and machine learning to forecast future results. The predictive analytics segment is expanding due to new advances technology of artificial intelligence and data miming tools, SAS Advanced Analytics and SAP Analytics Cloud is the top tool used in fraud detection.
The technique of using data to decide on the best course of action is known as prescriptive analytics. The growth of global healthcare fraud detection is expanding as various new techniques are developing.
The introduction of cutting-edge fraud identity management software is expected to boost the market growth. Massive amounts of data can be examined by machine learning to help create rules. This helps propel the market growth. Account auditing and investigation by a detective can help in healthcare fund misuse detection. The market for global healthcare fraud detection will grow rapidly, as the various new software based on data mining and artificial intelligence are being used by the healthcare industry. Furthermore, healthcare fraud detection market will also advance due to the expansion of analysis, services, insurance claim reviews and by maintaining payment integrity.
On the other hand, data security concern in healthcare industry may restrain the expansion of the global healthcare fraud detection market. The need for healthcare fraud detection significantly decreased after the COVID-19 pandemic. The focus of medical professionals, governments, and the general public has moved towards the virus's spread as a result of the fatal virus's quick expansion. It consequently decreased the need for fraud management detection. As a result, the COVID-19 pandemic caused severe disruptions in the market of the healthcare fraud detection.
By type, the descriptive analytics segment dominated the market in 2021. The factors responsible for the product segment growth are new tools developed in recent years. Furthermore, the introduction of Enblick data computing platform for data sorting in minimum time. Increased demand and approval of new tools supported the segment growth during forecast period.
By component, the software segment dominated market in 2021 and is expected to remain dominant during the forecast period. The use of numerous software contribute toward the market growth of healthcare fraud detection. The newly developed software namely SEON and LexisNexis also used widely in management of fraud detection.
By application, the insurance claims review segment dominated the market in 2021. The fraudulence in this segment is at the peak hence this segment dominated the in the global healthcare fraud detection market.
By end user, the healthcare payer segment dominated the market in 2021 and is expected to remain dominant during the forecast period. The market growth of this segment driven by the increased fraudulence in the public and private payers. The highest fraudulence cases in healthcare insurance and claims responsible for the market growth of healthcare payer
Region wise, North America has the highest market share during the forecast period. North America advances due to availability of newly developed software and high investigational cases of medical fraudulence in the U.S and Mexico.
Key Findings of the Study
- On the basis of type, the descriptive analytics segment dominated the market in 2021.
- On the basis of component, the software segment dominated the market in 2021.
- On the basis of application, the insurance claim review segment dominated the market in 2021.
- On the basis of end user, the healthcare payer segment dominated the market in 2021.
- On the basis of region, North America dominated the market in 2021.
Companies Mentioned
- International Business Machines Corporation (Ibm)
- Optum Inc.
- Verscend Technologies
- Mckesson Corporation
- Fair Isaac Corporation
- Sas Institute Inc.
- Hcl Technologies
- Wipro Limited
- Conduent
- Cgi Group
- Dxc Technology Company
- Unitedhealth Group, Inc.
- Exlservice Holdings Inc.
- Cotiviti Inc.
- Lexisnexis
- Osp Labs
- Northrop Grumman
- Northrop Grumman Corp
Methodology
The analyst offers exhaustive research and analysis based on a wide variety of factual inputs, which largely include interviews with industry participants, reliable statistics, and regional intelligence. The in-house industry experts play an instrumental role in designing analytic tools and models, tailored to the requirements of a particular industry segment. The primary research efforts include reaching out participants through mail, tele-conversations, referrals, professional networks, and face-to-face interactions.
They are also in professional corporate relations with various companies that allow them greater flexibility for reaching out to industry participants and commentators for interviews and discussions.
They also refer to a broad array of industry sources for their secondary research, which typically include; however, not limited to:
- Company SEC filings, annual reports, company websites, broker & financial reports, and investor presentations for competitive scenario and shape of the industry
- Scientific and technical writings for product information and related preemptions
- Regional government and statistical databases for macro analysis
- Authentic news articles and other related releases for market evaluation
- Internal and external proprietary databases, key market indicators, and relevant press releases for market estimates and forecast
Furthermore, the accuracy of the data will be analyzed and validated by conducting additional primaries with various industry experts and KOLs. They also provide robust post-sales support to clients.
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Table Information
| Report Attribute | Details |
|---|---|
| No. of Pages | 310 |
| Published | July 2022 |
| Forecast Period | 2021 - 2031 |
| Estimated Market Value ( USD | $ 1098.2 million |
| Forecasted Market Value ( USD | $ 3600 million |
| Compound Annual Growth Rate | 12.6% |
| Regions Covered | Global |
| No. of Companies Mentioned | 18 |
