Fraud Detection and Prevention Market 2017 by Solution, Service, Application Area, Organization Size, Vertical, and Region – Global Forecast to 2022

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The Fraud Detection and Prevention (FDP) market is expected to grow from USD 16.62 Billion in 2017 to USD 41.59 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 20.1%.

The increasing fraudulent activities in various industries and the increase in revenue and reputation loss for organizations are said to be the main drivers of the fraud detection and prevention market. The FDP market is segmented by solution, service, application area, deployment mode, organization size, vertical, and region. The FDP market by solution includes fraud analytics (predictive analytics, customer analytics, social media analytics, big data analytics, and behavioral analytics), authentication (Single-Factor Authentication (SFA) and Multi-Factor Authentication (MFA)), Governance, Risk, and Compliance (GRC) solution, and others (account management and fraud investigation).

The authentication solution segment in the FDP market is expected to have the largest market size during the forecast period. The market for the services segment is expected to be growing, as the individuals, Small and Medium-sized Enterprises (SMEs), and large enterprises are concerned about the secured access to their payment services. The professional services segment is expected to have the largest market share and dominate the FDP market during the forecast period.

The SMEs segment is expected to grow at the highest CAGR during the forecast period, owing to the increasing incidences of data breaches on these enterprises, as well as, for the need to deploy advanced FDP solutions. SMEs are small in terms of their size, but cater to a large number of customers globally. Robust and comprehensive security solutions are not implemented in SMEs, due to financial constraints in these organizations. However, the large enterprises segment accounts for the largest share of the fraud detection and prevention market in 2017.

FDP solutions have been deployed across various verticals, including the government and public utilities, retail, Banking, Financial Services, and Insurance (BFSI), telecommunications, healthcare, real estate, and others (travel and transportation, media and entertainment, and life sciences). The government and public utilities vertical is expected to witness the highest CAGR during the forecast period. However, BFSI is estimated to have largest market size in 2017.

Market Dynamics

Drivers

  • Increasing Fraudulent Activities in Various Industries
  • Increase in Reputation Loss and Revenue Loss for Organizations
  • Increasing Online Transactions Over Mobile and Web Applications

Restraints

  • Lack of Integration Capabilities

Opportunities

  • Emerging Economies
  • Introduction of AI and Machine Learning Technologies for Detecting Frauds

Challenges

  • Low Levels of Awareness About the Fraud Possibilities in SMES
  • Early Detection of Fraudulent Activities
  • High Cost in Deployment of Fdp Solutions

Key Topics Covered:

1 Introduction

2 Research Methodology

3 Executive Summary

4 Premium Insights

5 Market Overview and Industry Trends

6 Fraud Detection and Prevention Market Analysis, By Solution

7 Fraud Detection and Prevention Market Analysis, By Service

8 Market Analysis, By Application Area

9 Fraud Detection and Prevention Market Analysis, By Deployment Mode

10 Market Analysis, By Organization Size

11 Fraud Detection and Prevention Market Analysis, By Vertical

12 Geographic Analysis

13 Competitive Landscape

14 Company Profiles

  • ACI Worldwide, Inc.
  • BAE Systems
  • DXC Technology (CSC)
  • Easy Solutions, Inc.
  • Experian Information Solutions, Inc.
  • Fair Isaac Corporation
  • Featurespace Limited
  • Fiserv, Inc.
  • Friss
  • International Business Machines Corporation
  • Lexisnexis
  • Nice Systems Ltd.
  • SAP SE
  • SAS Institute
  • Sekur Me
  • Threatmetrix, Inc.
  • Webroot Inc.

For more information about this report visit https://www.researchandmarkets.com/research/m7hcj4/fraud_detection

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