Global Employee Fraud Detection Market Report and Forecast 2023-2028

According to the report, the global employee fraud detection market is projected to grow at a CAGR of 21.50% between 2023 and 2028. Aided by the growing demand for advanced fraud detection and prevention solutions and the increasing application of these solutions across various industries, the market is expected to grow significantly by 2028.

Employee fraud detection refers to the strategies and solutions employed by businesses to identify and prevent dishonest activities carried out by their employees. These activities may include theft, embezzlement, bribery, and other corrupt practices. With the increasing integration of technology into business operations, the scale and sophistication of such fraudulent activities have grown exponentially, making fraud detection an essential aspect of business strategy.

The increasing demand for sophisticated fraud detection and prevention solutions is a significant driver of the global employee fraud detection market growth. The growing awareness of the financial and reputational damage caused by employee fraud has led to a shift towards the adoption of advanced fraud detection strategies. Moreover, the rising complexity and sophistication of fraudulent activities necessitate the deployment of advanced solutions, thereby fuelling market growth.

The expanding application of fraud detection solutions across various industries also plays a critical role in propelling the employee fraud detection market development. In sectors like finance, healthcare, retail, and telecommunications, where large volumes of sensitive data are handled daily, the deployment of fraud detection solutions is essential. These solutions not only help identify fraudulent activities but also aid in maintaining regulatory compliance and safeguarding customer trust.

Furthermore, the emergence of advanced technologies such as artificial intelligence (AI), machine learning (ML), and data analytics has greatly enhanced the capabilities of fraud detection solutions. These technologies enable the analysis of vast amounts of data to identify patterns and anomalies, which can indicate potentially fraudulent activities, thereby boosting the employee fraud detection market expansion.

Moreover, the increasing prevalence of remote work due to the COVID-19 pandemic has further intensified the need for robust employee fraud detection solutions. With employees working outside the traditional security perimeters of office premises, the risk of fraud has increased significantly. This trend has led to a surge in demand for fraud detection solutions that can effectively monitor remote working environments, thus propelling the employee fraud detection market growth.

Market Segmentation

The market can be divided based on solution, deployment, application, end use, and region.

Market Breakup by Solution

• Behavioural Analytics
• Real-Time Transaction Screening
• Real-Time Reporting
• Others

Market Breakup by Deployment

• On-Premise
• Cloud

Market Breakup by Application

• Vendor Fraud
• Data Theft
• Payroll Fraud
• Accounting Fraud
• Asset Misappropriation
• Bribery and Corruption

Market Breakup by End Use

• IT and Telecommunication
• Retail and Consumer Packed Food
• BFSI
• Health and Life sciences
• Media and Entertainment
• Construction and Real Estate
• Travel and Transportation
• Energy and Utilities
• Others

Market Breakup by Region

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East and Africa

Competitive Landscape

The report looks into the market shares, plant turnarounds, capacities, investments, and acquisitions and mergers, among other major developments, of the global employee fraud detection companies. Some of the major key players explored in the report are as follows:

• IBM Corporation
• NICE Ltd.
• ACI Worldwide, Inc.
• Fiserv, Inc.
• Infosys Limited
• Securonix, Inc.
• Others

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*The publisher always strives to provide you with the latest information. The numbers in the article are only indicative and may be different from the actual report.