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In recent years, there have been so many significant recent developments in medical payment fraud detection markets as they respond to increasingly sophisticated payment system complexity among healthcare payers and rising levels of fraudulent activities. Over the past few years, there has been a noted increase in use of advanced technologies and software for detecting or preventing medical bill frauds. Additionally; another very notable trend is artificial intelligence (AI). This form of technological advancement helps discover irregularities within huge amounts of medical data thus indicating where acts related to fraud come in using machine learning (ML) algorithms processes. As fraudsters grow smarter through time, integrating AI as well as ML becomes key.
Another trend worth noting is real-time detection rather than after occurrence action taking place fifteen days later. Given how rapidly fraud tactics evolve compared to traditional retrospective measures; organizations providing care are now investing heavily on platforms that assist them locate suspicious incidents almost immediately they happen . Thus, minimizing financial losses they would have incurred due to delayed interventions at times when such delays were not affordable at all. In health sector, such quick responses even guard patients’ data reliability and ensure that unauthorized entrants do not get access to sensitive information.
Interoperability and integration are other market trends of great concern. Payment systems in healthcare are becoming more interlinked so criminals discover the weaknesses within multiple points of contact. Thus, current demand for fraud detection software which can blend with established health IT infrastructure is increasing rapidly. Interconnected and interoperable systems improve the efficiency with which fraud detection works since they provide a holistic view of whole payment ecosystem thereby enabling organizations to query even across different channels and systems.
Market dynamics have also been significantly influenced by the regulatory environment. Governmental and regulatory bodies have put measures in place to ensure healthcare payments are safe and reliable from external threats like hacking . For instance; healthcare organizations must comply with these laws hence an increase in adoption of compliant anti-fraud bills .This level of adaptation ensures safety among participants as well as system users including patients themselves.
Cloud-based solutions are gaining popularity in Medical Payment Fraud Detection Market all over the world. Scalability, versatility, and cost effectiveness of cloud based platforms makes them attractive to health care providers that require efficient dynamic fraud detection capacities. Clouds allow for real time updates that can be deployed fast with ease thus supporting seamless collaboration across several locations so as to meet new industry needs.
Medical Payment Fraud Detection Market Highlights:
Global Medical Payment Fraud Detection Market Overview
Medical Payment Fraud Detection Market Size was valued at USD 1.2 billion in 2022. The medical payment fraud detection market industry is projected to grow from USD 1.45 billion in 2023 to USD 6.822 billion by 2032, exhibiting a compound annual growth rate (CAGR) of 21.30% during the forecast period (2023 - 2032). The market is expanding due to market drivers like the rising prevalence of health insurance and the rise in medical payment fraud instances.
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
In February 2024, BharatGPT and Vizzhy are about to announce the launch of Healthcare LLM; VizzhyGPT is a multimodal model with a vision of automating diverse hospital processes in the clinical and non-clinical realm.
On the other side, Healthcare Fraud Shield (HCFS), one of the key organizations offering fraud, waste, abuse, and error (FWAE) protection solutions to insurers in the healthcare market, presented FWA360Leads® which is their latest product in January 2024, determines priorities and criticality of frauds as per the degree of severity and importance.
In May 2023, Teradata, alongside FICO, announced that they would bring to market integrated advanced analytics offerings that specifically target supply chain optimization, insurance claims and real-time payment fraud. With data integration into a single environment for analyses, decision-making becomes quicker and more accurate since all relevant data points can be accessed within seconds across various industries like finance, health care, retailing, manufacturing, and travel.
Payrailz® Fraud Monitor was newly introduced by Jack Henry™ as an AI-based cloud-native component within the Payrailz Digital Payments Platform in June 2023. Essentially, this tool screens all payment information from when the transaction is initiated for any signs of irregularities or suspicious elements.
Veriff unveiled its lineup of new biometrics-powered identity verification solutions built specifically for the healthcare sector in March 2022. Rather than using passwords alone to verify users’ identities online or through mobile apps, Veriff’s new solution employs artificial intelligence (AI) and facial recognition for user identification purposes.
The Canadian Life and Health Insurance Association (CLHIA) launched an industry initiative in February 2022 aimed at pooling claims data together with utilizing advanced artificial intelligence capabilities to enhance detection mechanisms as well as investigate benefits frauds.
This development has boosted Wipro FullStride Cloud Services following Wipro Limited's acquisition of LeanSwift in December 2021.
Artivatic also introduced its new ALFRED-AI HEALTH CLAIMS platform in June 2021 that enables end-to-end automation of health claims with a fraud and abuse rate of 30% plus. Moreover, the ALFRED-AI HEALTH CLAIMS system can be self-taught to create a superior risk assessment system and detect fraud besides making a better decision.
Medical Payment Fraud Detection Market Trends
- Growing obese population is driving the market growth
The market CAGR for medical payment fraud detection is expanding as a result of a significant number of fraudulent actions in the healthcare industry. Fraud based on deception or misrepresentation can be committed by healthcare professionals, patients, and other individuals who purposefully trick the healthcare system into granting them illegal advantages. Kickbacks, billing, invoicing for services that were never rendered, medical testing, and other fraudulent practices are all part of this fraud and abuse. In 2021, the National Health Care Anti-Fraud Association projected that medical payment fraud costs the country roughly $68 billion year, or about 3% of the $2.26 trillion in health care spending, according to Blue Cross Blue Shield Association, a US-based federation. According to other estimates, the amount might reach $230 billion, or 10% of annual health care spending. Consequently, the market for medical payment fraud detection is expanding as a result of the rising number of fraudulent activities in the field of medicine.
A prominent trend gaining traction in the medical payment fraud detection market is the adoption and development of new technologies. To bolster their market position, the main corporations are concentrating on releasing products and services that are driven by statistical data analysis and artificial intelligence (AI). These statistical operations include data mining, regression analysis, machine learning, pattern recognition, supervised learning, and unsupervised learning. These fraud detection approaches also do other statistical tasks. For instance, Codoxo, a US-based AI-driven healthcare solution, introduced its healthcare integrity suite in December 2020. This suite offers health agencies unique insights and solutions for identifying risks and controlling costs in clinical care, provider education, and special investigative units, network management and payment integrity. The suite application comprises fraud, network, provider, insight, clinical, and payment scope. Thus, driving the medical payment fraud detection market revenue.
Medical Payment Fraud Detection Market Segment Insights
Medical Payment Fraud Detection Type Insights
The medical payment fraud detection market segmentation, based on type includes Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics. The descriptive analytics segment dominated the market due to its widespread use and simplicity. It uses both recent and historical data to find trends and connections. This improves the process of identifying potential scams. Additionally, it serves as a foundation for the efficient use of prescriptive and predictive analytics. This helps the segment's expansion even more.
Figure 1: Medical Payment Fraud Detection Market, by Type, 2022 & 2032 (USD billion)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Medical Payment Fraud Detection Component Insights
The medical payment fraud detection market segmentation, based on component, includes Services and Software. The services category generated the most income. The detection of fraudulent activity in the delivery of medical services is known as service medical payment fraud detection. It involves charging for goods or services that are not received and billing for services that are not provided. The payment of kickbacks and bribes by service providers to refer patients to their facilities is another type of service healthcare fraud.
Medical Payment Fraud Detection Delivery Mode Insights
The medical payment fraud detection market segmentation, based on delivery mode, includes On-premise and Cloud-based. The on-premise category generated the most income because data is readily accessible on the website, i.e., hospitals, etc., which has led to better record management and data monitoring, among other things. The current technologies are useful in small organisations, but when scaled up, they can make data management challenging and laborious if the organization works with a sizable dataset. This could entail a substantial financial outlay for data security and storage.
Medical Payment Fraud Detection Source of Service Insights
The medical payment fraud detection market segmentation, based on source of service, includes In-house and Outsourced. The outsourced category generated the most income. Medical billing services are third parties providers can use to outsource their medical payment. As compensation for handling several facets of the clinic's revenue cycle management, these billing services often take a percentage of a practice's collections.
Medical Payment Fraud Detection End-User Insights
The medical payment fraud detection market segmentation, based on end-user, includes Private Insurance Payers, Public/Government Agencies, and Third-Party Service Providers. The private insurance payers category generated the most income because more individuals are purchasing health insurance; it also causes an increase in the amount of false claims. Prepayment review and post-payment review are further divisions of the segment.
Medical Payment Fraud Detection Regional Insights
By region, the study provides the market insights into North America, Europe, Asia-Pacific and Rest of the World. The North American medical payment fraud detection market area will dominate this market due to factors including the high healthcare spending per capita, the sizable elderly and sick population, the high number of persons with health insurance, the prevalence of medical payment fraud, the favorable government anti-fraud programs, and the push to lower healthcare costs. The expansion of the business in the region is also being aided by the rise in service providers and technological developments in software designed to catch such misconduct.
Further, the major countries studied in the market report are The US, Canada, German, France, the UK, Italy, Spain, China, Japan, India, Australia, South Korea, and Brazil.
Figure 2: MEDICAL PAYMENT FRAUD DETECTION MARKET SHARE BY REGION 2022 (%)
Source: Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe medical payment fraud detection market accounts for the second-largest market share due to improvements in the health infrastructure of the surrounding nations, an increase in the prevalence of infectious diseases, and favorable reimbursement policies. Further, the German medical payment fraud detection market held the largest market share, and the UK medical payment fraud detection market was the fastest growing market in the European region
The Asia-Pacific Medical payment fraud detection Market is expected to grow at the fastest CAGR from 2023 to 2032 due to the existence of major industry players as well as the increased adoption of cutting-edge medical imaging equipment and software in developing nations like India and China. Moreover, China’s medical payment fraud detection market held the largest market share, and the Indian medical payment fraud detection market was the fastest growing market in the Asia-Pacific region.
Medical Payment Fraud Detection Key Market Players & Competitive Insights
Leading market players are investing heavily in research and development in order to expand their product lines, which will help the medical payment fraud detection market, grow even more. Market participants are also undertaking a variety of strategic activities to expand their footprint, with important market developments including new product launches, contractual agreements, mergers and acquisitions, higher investments, and collaboration with other organizations. To expand and survive in a more competitive and rising market climate, medical payment fraud detection industry must offer cost-effective items.
Manufacturing locally to minimize operational costs is one of the key business tactics used by manufacturers in the medical payment fraud detection industry to benefit clients and increase the market sector. In recent years, the medical payment fraud detection industry has offered some of the most significant advantages to medicine. Major players in the medical payment fraud detection market attempting to increase market demand by investing in research and development operations include LexisNexis Risk Solutions, International Business Machines Corporation, Optuminsight, OSP Labs, DXC Technology Company, Unitedhealth Group, SAS Institute, Fair Isaac Corporation, EXL Service Holdings, Inc., and CGI GROUP.
Data management and business intelligence software services are offered by SAS Institute Inc (SAS). The company's solution portfolio comprises advanced analytics solutions, AI, ML, cloud, data management, decisioning, fraud and security intelligence, IoT, marketing analytics, operationalizing analytics, and risk management. Agriculture, banking, education, healthcare, insurance, the life sciences, manufacturing, the public sector, retail and consumer goods, small and midsize businesses, sports, communications, media and technology, and utilities are just a few of the sectors SAS supports.
A provider of consultancy services and information technology (IT), DXC Technology Co. The company's service portfolio comprises workplace and mobility solutions, analytics, cloud applications, cloud infrastructure, corporate apps, data security services, and IT outsourcing (ITO). It additionally offers its services via a network of partners. DXC provides services to the insurance, healthcare, life sciences, aerospace, defence, consumer, retail, manufacturing, travel, hotel, utilities, oil and gas, technology, media, and telecommunications sectors, as well as the public, banking, and capital markets.
Key Companies in the medical payment fraud detection market include
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International Business Machines Corporation
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Optuminsight
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OSP Labs
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DXC Technology Company
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Unitedhealth Group
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Fair Isaac Corporation
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EXL Service Holdings, Inc.
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CGI GROUP
Medical Payment Fraud Detection Industry Developments
June 2020: WhiteHatAI was purchased by Sharecare, an Atlanta-based digital health startup, for an unknown sum. By acquiring WhiteHatAI, a portfolio-based AI-driven suite that assists in detecting FWA before it happens, Sharecare will be able to increase the efficiency and effectiveness of healthcare organizations. Healthcare artificial intelligence firm WhiteHatAI is in the US and focuses on preventing fraud, waste, and abuse in healthcare payments.
Medical Payment Fraud Detection Market Segmentation
Medical Payment Fraud Detection Type Outlook
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Descriptive Analytics
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Predictive Analytics
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Prescriptive Analytics
Medical Payment Fraud Detection Component Outlook
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Services
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Software
Medical Payment Fraud Detection Delivery Mode Outlook
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On-premise
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Cloud-based
Medical Payment Fraud Detection Source of Service Outlook
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In-house
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Outsourced
Medical Payment Fraud Detection End-User Outlook
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Private Insurance Payers
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Public/Government Agencies
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Third-Party Service Providers
Medical Payment Fraud Detection Regional Outlook
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North America
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US
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Canada
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Europe
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Germany
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France
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UK
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Italy
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Spain
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Rest of Europe
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Asia-Pacific
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China
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Japan
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India
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Australia
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South Korea
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Australia
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Rest of Asia-Pacific
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Rest of the World
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Middle East
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Africa
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Latin America
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