In 2016, the global market size for Fraud Detection and Prevention was estimated at USD 13 million and is expected to reach USD 40 million by 2023, increasing at a Common Annual Growth Rate (CAGR) of 17 percent over the forecast period. Any illegal act involving the willful manipulation of someone with an unfair and unlawful motive for financial or personal gain is called fraud. Fraud detection and prevention systems are computer programs that are used to provide analytical approaches to fraud cases and to help identify and prevent future crimes.
Through evaluating current data, predictive analytics tools help companies determine the possibilities of fraud events. The tools are used to identify potential risks, payment fraud, insurance fraud, and credit/debit card fraud. Organizations are seeking to impart these approaches to identify fraud or suspicious activity and their trends to help reduce fraud-related losses significantly. Big data analytics is an innovative analytical tool that protects proactively against fraudulent activities in order to detect, avoid and investigate fraud. To identify and prevent fraud, various industries, such as insurance, banking, and healthcare, are applying big data analytics.
The vertical BFSI is a major target for cyber criminals as it holds confidential worker, client, property, office, branch, and operational data. Because of its large amount of transactions (both monetary and data-centric), number of transactions, technological advances, and financial sector digitalization, the probability of vertical fraud is growing substantially. The technology makes for more efficient, faster, and more effective fraud detection efforts to create a positive difference.
- IBM Corporation (U.S.)
• Oracle Corporation (U.S.)
• Fico (Brazil)
• SAS Institute Inc. (U.S.)
• SAP SE (Germany)
• Computer Sciences Corporation (U.S.)
• BAE Systems (U.K.)
• ACI Worldwide (U.S.)
• Fiserv Inc. (U.S.)
• Threatmetrix (U.S.)
The global market for fraud detection and prevention is segmented according to the type of solution, products, method of implementation, the end user, vertical industry, and geography. The market is divided into fraud analysis and encryption based on the type of solution. Managed and professional services are included in the report. The market is divided into cloud and on-site systems depending on the implementation framework. It is classified into small and medium-sized enterprises (SMEs) and large enterprises (LE) by end users. It is listed in banking, final services & insurance (BFSI) by vertical, industry, retail, healthcare, property, manufacturing, and others.
It is estimated that North America has the largest market share for fraud detection and prevention per country in the FDP industry. Increasing revenue loss due to attacks on vulnerable organizations, early adoption of digital technologies like AI, IoT, fraud detection machine learning, and the emergence of several FDP solution providers may lead to North America’s market growth. Increasing smartphone deep penetration along with the growing demand for ecommerce transactions, organizations are implementing FDP solutions to protect their organizational data from any local fraud. Strong presence of vendors through software acquisitions, alliances, and collaborations with device integrators, suppliers, and resellers would further contribute to North America’s overall market development.
In 2016, the professional services sector dominated the market for fraud detection and prevention, accounting for about 54.9 percent of the market due to higher fraudulent activities and data security norms imposed by government. However, growth in mobile device use presents unique challenges for business and government agencies, enforcing them to adopt effective solutions that would protect, detect, and respond to newer threats that are emerging. BFSI reported the highest revenue in 2016, accounting for approximately USD 3,498 million due to increased adoption of fraud detection & prevention solutions due to a high demand to improve customer authentication processes.
Table Of Content:
Chapter 1. Report Prologue
Chapter 2. Market Introduction
Chapter 3. Research Methodology
Chapter 4. Market Dynamics
Chapter 5. Market Factor Analysis
Chapter 6. Global, By Type
Chapter 7. Global By Treatment
Chapter 8. Global By End Users
Chapter 9. Global By Region
Chapter 10. Company Landscape
Chapter 11 Company Profiles
Chapter 12 MRFR Conclusion
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