The Global Fraud Risk Management Services Market 2018-2022 to grow at a CAGR of 18.25% during the period 2018-2022.
Global Fraud Risk Management Services Market 2018-2022, has been prepared based on an in-depth market analysis with inputs from industry experts. The report covers the market landscape and its growth prospects over the coming years. The report also includes a discussion of the key vendors operating in this market. To calculate the market size, the report considers the revenue generated from the sale of this solution to SMEs and large enterprises.
Fraud risk management services prevent fraudsters from gaining unauthorized access; by verifying the user's identity, these services aid in protecting enterprise against frauds at the early stages, thus eliminating such activities.
According to the report, one driver influencing this market is the growing demand for better detection accuracy at lower costs. One trend affecting this market is the use of analytics in fraud detection. Further, the report states that one challenge affecting this market is the lack of awareness among enterprises.
Key questions answered in this report
What will the market size be in 2022 and what will the growth rate be?
What are the key market trends?
What is driving this market?
What are the challenges to market growth?
Who are the key vendors in this market space?
What are the market opportunities and threats faced by the Key vendors?
What are the strengths and weaknesses of the key vendors?
Key Topics Covered:
PART 01: EXECUTIVE SUMMARY
PART 02: SCOPE OF THE REPORT
PART 03: RESEARCH METHODOLOGY
PART 04: MARKET LANDSCAPE
PART 05: MARKET SIZING
Market sizing 2017
Market size and forecast 2017-2022
PART 06: FIVE FORCES ANALYSIS
PART 07: CUSTOMER LANDSCAPE
PART 08: MARKET SEGMENTATION BY END-USER
Segmentation by end-user
Comparison by end-user
Market opportunity by end-user
PART 09: REGIONAL LANDSCAPE
PART 10: DECISION FRAMEWORK
PART 11: DRIVERS AND CHALLENGES
PART 12: MARKET TRENDS
Use of analytics in fraud detection
Use of behavioral biometrics to detect fraudsters
Use of big data and machine learning to combat online fraud