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M2M Fraud and Revenue Leakage Market and Forecast 2013 - 2018

M2M Fraud and Revenue Leakage Market and Forecast 2013 - 2018

The forecast for Machine-to-Machine (M2M) is set to nearly triple through 2018. One of the great allures of M2M is the many and varied use cases including everything from smart meters, interactive kiosks, surveillance cameras, and more. The business drivers include everything from proactive maintenance, production assurance, theft reduction, productivity improvement, etc.

It important to note that the steep growth curve is yet to begin, as M2M is expected to take off significantly with the so-called Internet of Things (IoT). M2M has become much more complex and “smart” due to major advances in semiconductor and software with the potential to be embedded in virtually any asset or object requiring monitoring and control throughout the enterprise. By way of example, industry giant Cisco is aggressively forecasting about 50 billion devices will be connected by 2020, after coming out with an earlier analysis in January that claimed 8.7 billion connected devices in 2012.

With this dramatic growth expectation, there is a critical need to focus on potential lost revenue and fraud that may occur within various portions of the M2M ecosystem. This research assesses risk management issues in M2M, key companies, solutions, and market positioning. The report provides a market driver analysis along with anticipated revenues through 2020.

Target Audience:

  • Mobile network operators
  • Managed services providers
  • Systems integration companies
  • Application developers and ASP
  • Network integration companies
  • Network infrastructure providers
  • Enterprise companies of all types
  • Investment and M&A companies of all types
  • M2M equipment and service providers of all types


General Methodology

Mind Commerce Publishing's research methodology encompasses input from a wide variety of sources.

We rely heavily upon our Subject Matter Experts (SME) in terms of their market knowledge, unique perspective, and vision. We utilize SME industry contacts as well as previous customers and participants in our market surveys and interactive interviews.

In addition, we rely upon our extensive internal database, which contains modeling, qualitative analysis, and quantitative data. We review secondary sources and compare to our primary sources to update previous findings (for prior version reports) and/or compile baseline information for technology and market modeling.

We share preliminary models with industry contacts (select previous clients, experts, and thought leaders) to verify the veracity of initial modeling. Prior to final report production (analysis, findings, and conclusions), we engage in an internal review with internal SMEs as well as cross-expertise, senior staff members to challenge results.

We believe that forecasts should be prepared as part of an integrated process which involves both quantitative as well as qualitative factors. We follow the following 3-step process for forecasting.

Forecasting Methodology

Step 1 - Forecasts Input: The inputs for the present and historical revenues are derived from industry players. Financial and other quantitative data for individual sub-market categories are derived from original research and tested with interviews with major industry constituents.

Step 2 - Forecasting of Future Years: Mind Commerce extends forecasts based on a variety of factors including demand drivers as well as supply side data. Key success factors and assumptions are considered.

Step 3 - Validation of Data: The final step is to validate projections, which is accomplished in consultation with both internal and external industry experts, including both topic and regional experts. Adjustments are made to the forecasts based on factors identified throughout this process.


1.0 Executive Summary
2.0 Overview Of Telecom Fraud Management
2.1 Fraud Management For Telecom Operators
2.2 Fraud Management Strategy
2.2.1 Empowerment
2.2.2 Controls Coverage
2.2.3 Ownership
2.2.4 Responsibility Gap
2.3 Basics Of Fraud Management Strategies
2.3.1 People
2.3.2 Process
2.3.3 Technology
2.4 Fraud Management System (Fms)
2.4.1 Advantages Of Fraud Management System (Fms)
2.4.2 Fraud Management In M2m
3.0 Overview Of M2m
3.1 M2m Applications
3.1.1 Mobile Operators Role
3.1.2 M2m And Smart Grid
3.1.3 Transportation
3.1.4 Road Traffic
3.1.5 Parking Meters
3.1.6 Container
3.1.7 Security Systems
3.1.8 Healthcare
3.1.9 “big Data” Analytics
3.2 M2m Technologies
3.2.1 Cellular Technologies
3.2.2 Satellite
3.2.3 Wi-fi
3.2.4 Bluetooth
3.2.5 Zigbee
3.2.6 Affordable Geo-location
3.2.7 Lower Cost Specialized Sensors
3.2.8 Affordable Integrated, Special-purpose Devices
4.0 Risk Management And Revenue Assurance Issues In M2m
4.1 Revenue Assurance
4.1.1 Lost Sim Cards
4.1.2 The Problem
4.1.3 Solutions
4.2 Risk Management
4.2.1 Security In M2m
4.2.2 Need For End-to-end Security
4.3 M2m Security Is Key To Industry Verticals
4.3.1 Privacy In M2m
5.0 Companies And Solutions
5.1 Netezza / Ibm
5.1.1 Company Overview
5.1.2 Location
5.1.3 Industry Classification
5.1.4 Business Description
5.1.5 Company History
5.1.6 Key People
5.1.7 Company Updates
5.1.8 Key Developments
5.1.9 Mergers And Acquisitions
5.1.10 Company Analysis
5.1.11 Swot Analysis
5.1.12 Strengths
5.1.13 Weaknesses
5.1.14 Opportunities
5.1.15 Threats
5.1.16 Interview With Mind Commerce
5.1.17 Company’s Analysis
5.1.18 Netezza And M2m Fraud And Revenue Leakage
5.2 Teredata
5.2.1 Company Overview
5.2.2 Location
5.2.3 Industry Classification
5.2.4 Business Description
5.2.5 Company History
5.2.6 Key People
5.2.7 Company Updates
5.2.8 Key Developments
5.2.9 Mergers And Acquisitions
5.2.10 Company Analysis
5.2.11 Swot Analysis
5.2.12 Strengths
5.2.13 Weaknesses
5.2.14 Opportunities
5.2.15 Threats
5.2.16 Company’s Business Strategy
5.2.1 Interview With Mind Commerce
5.2.2 Company’s Analysis
5.3 Oracle
5.3.1 Company Information
5.3.2 Location
5.3.1 Business Description
5.3.2 Company History
5.3.3 Key People
5.3.4 Mergers And Acquisitions
5.3.5 Company Analysis
5.3.6 Swot Analysis
5.3.7 Strengths
5.3.8 Weaknesses
5.3.9 Opportunities
5.3.10 Threats
5.3.1 Company’s Analysis
5.4 Sap
5.4.1 Company Overview
5.4.2 Location
5.4.3 Industry Classification
5.4.4 Business Description
5.4.5 Company History
5.4.6 Key People
5.4.7 Mergers And Acquisitions
5.4.8 Company Analysis
5.4.9 Swot Analysis
5.4.10 Strengths
5.4.11 Weaknesses
5.4.12 Opportunities
5.4.13 Threats
5.4.14 Company’s Business Strategy
5.4.1 Interview With Mind Commerce
5.4.2 Company’s Analysis
5.5 Sas
5.5.1 Company Overview
5.5.2 Location
5.5.3 Industry Classification
5.5.4 Business Description
5.5.5 Company History
5.5.6 Key People
5.5.7 Company Updates
5.5.8 Mergers And Acquisitions
5.5.9 Company Analysis
5.5.10 Swot Analysis
5.5.11 Strengths
5.5.12 Weaknesses
5.5.13 Opportunities
5.5.14 Threats
5.5.1 Interview With Mind Commerce
5.5.2 Company’s Analysis
5.6 Agilis International
5.6.1 Company Overview
5.6.2 Location
5.6.3 Industry Classification
5.6.4 Business Description
5.6.5 Key People
5.6.6 Company Updates
5.6.7 Mergers And Acquisitions
5.6.8 Company Analysis
5.6.9 Swot Analysis
5.6.10 Strengths
5.6.11 Weaknesses
5.6.12 Opportunities
5.6.13 Threats
5.6.14 Company’s Business Strategy
5.6.1 Interview With Mind Commerce
5.6.2 Company’s Analysis
5.7 Tableau
5.7.1 Company Overview
5.7.2 Location
5.7.3 Industry Classification
5.7.4 Business Description
5.7.5 Company History
5.7.6 Key People
5.7.7 Company Analysis
5.7.8 Swot Analysis
5.7.9 Strengths
5.7.10 Weaknesses
5.7.11 Opportunities
5.7.12 Threats
5.7.13 Company’s Business Strategy
5.7.1 Interview With Mind Commerce
5.7.2 Company’s Analysis
5.8 Wedo Technologies
5.8.1 Company Overview
5.8.2 Location
5.8.3 Industry Classification
5.8.4 Business Description
5.8.5 Company History
5.8.6 Key People
5.8.7 Mergers And Acquisitions
5.8.8 Company Analysis
5.8.9 Swot Analysis
5.8.10 Strengths
5.8.11 Weaknesses
5.8.12 Opportunities
5.8.13 Threats
5.8.1 Interview With Mind Commerce
5.9 Teoco
5.9.1 Company Overview
5.9.2 Location
5.9.3 Industry Classification
5.9.4 Business Description
5.9.5 Company History
5.9.6 Key People
5.9.7 Mergers And Acquisitions
5.9.8 Company Analysis
5.9.9 Swot Analysis
5.9.10 Strengths
5.9.11 Weaknesses
5.9.12 Opportunities
5.9.13 Threats
5.9.14 Company’s Business Strategy
5.9.1 Interview With Mind Commerce
5.10 Cvidya
5.10.1 Company Overview
5.10.2 Location
5.10.1 Industry Classification
5.10.2 Business Description
5.10.3 Service Offerings
5.10.4 Key Developments
5.10.5 Swot Analysis
5.11 Mach
5.11.1 Company Overview
5.11.2 Location
5.11.3 Industry Classification
5.11.4 Business Description
5.11.5 Company History
5.11.6 Key People
5.11.7 Mergers And Acquisitions
5.11.8 Company Analysis
5.11.9 Swot Analysis
5.11.10 Strengths
5.11.11 Weaknesses
5.11.12 Opportunities
5.11.13 Threats
5.11.14 Company’s Business Strategy
5.11.1 Interview With Mind Commerce
5.12 Overall Analysis
5.13 Market Survey Results
6.0 Market Outlook
6.1 Growth Driver Analysis Of M2m Solution Market
6.1.1 Emergence Of Alliances And Market Consolidations Will Help End Consumer
6.1.2 Unified M2m Development Platforms
6.1.3 Growth In Connected Consumer Electronic Devices
6.1.4 Launch Of New Home Automation Products And Diy Products
6.1.5 Growth In Potential End-use Applications Will Widen M2m Market Scope
6.1.6 Smart Grids Market Will Be A Major Contributor
6.1.7 Satellite M2m Communications Growth: Revenue Projection 2013-2018
6.1.8 Standards For Connected Cars And Demand For Telematics Segment
6.1.9 Growth In The Vas Applications Market
6.1.10 Deployment Of Industrial Wsns To Boost Overall Market
6.2 Global Cellular M2m Module Pricing 2014- 2018
6.3 Global M2m Market Sales Revenue 2014 – 2018
6.4 Global M2m Software Market Revenue 2014 – 2018
6.5 Global M2m Market Competitive Landscape 2013
6.6 Market Outlook For M2m Fraud And Revenue Leakage
6.7 M2m Market Global Business Impact (Bi)
6.7.1 Apac M2m Business Impact Revenue 2016-2020
6.7.2 Global M2m Business Impact Revenue In Regions 2016 – 2020
6.7.3 China M2m Business Impact Revenue 2016-2020
6.7.4 Japan M2m Business Impact Revenue 2016 - 2020
6.7.5 India M2m Business Impact Revenue 2016-2020
6.7.6 South Korea M2m Business Impact Revenue 2012-2020
Figures
Figure 1 M2M as a Fundamental Change Agent
Figure 2 Cellular Data Transmissions from Fixed or Mobile Assets
Figure 3 Sensors Networks in Practice
Figure 4 Wireless Sensor Communications Module by Libelium
Figure 5 Libelium’s pre-configured sensor board optimized for agriculture applications
Figure 6 Global M2M Market: End Use Applications
Figure 7 Conceptual Rending of M2M Platform
Figure 8 Global Smart Meter M2M Connections units 2010 – 2020
Figure 9: Global Satellite M2M Market Revenue 2011 – 2016
Figure 10 Month to Month Timeline Track of oneM2M Standard 2011-2012
Figure 11 Comparison between High Value and Current Operator Service Model
Figure 12 Global M2M Market, VAS Applications Share by % 2013
Figure 13 Global Cellular M2M Module Pricing ($) 2010-2014
Figure 14 Global Cellular M2M Module Pricing ($) 2014-2018
Figure 15 Global M2M Market Sales Revenues in USD $ billion 2014 – 2018
Figure 16 Graphical Presentation of Global M2M Market, Competitive Landscape by % 2013
Figure 17 Asia Pacific M2M Business Impact Revenues 2012 – 2020
Figure 18 Global M2M Business Impact by Region 2012 – 2020
Figure 19 China M2M Business Impact Revenues by Industry 2012 – 2020
Figure 20 Japan M2M Business Impact Revenues by Industry 2012 – 2020
Figure 21 India M2M Business Impact Revenues by Industry 2012 – 2020
Figure 22 Korea M2M Business Impact Revenues by Industry 2012 – 2020
Tables
Table 1 OVERVIEW OF MAIN WIRELESS COMMUNICATIONS USED IN M2M
Table 2 Bluetooth and ZigBee Comparison
Table 3 Major M&A Events in Global M2M Market 2010 – 2012
Table 4 Global Smart Meter M2M Connections Unit in Million 2010 – 2020
Table 5 Global Satellite M2M Market Revenue in USD $ billion 2011 – 2016
Table 6 Global Satellite M2M Operator Companies
Table 7 VAS Applications Share by % in Global M2M Market 2013
Table 8 Global Cellular M2M Module Pricings in USD $ 2014– 2018
Table 9 Global M2M Market Sales Revenues in USD $ billion 2011 – 2017
Table 10 Global M2M Software Market Revenues in USD $ million 2014 – 2018
Table 11: Global M2M Market, Competitive Landscape by % 2013
Table 12 Asia Pacific M2M Business Impact Revenues in USD $ billion 2016 – 2020
Table 13 Global M2M Business Impact Revenues by Region $B 2016 – 2020
Table 14 China M2M Business Impact Revenues by Industry in USD $ billion 2016 – 2020
Table 15 Japan M2M Business Impact Revenues by Industry 2016 – 2020
Table 16 India M2M Business Impact Revenues by Industry, 2016 – 2020
Table 17 Korea M2M Business Impact Revenues in USD $ billion by Industry 2016 – 2020

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