市場調査レポート - 236917

モバイル部門の収益保証・不正行為管理：ビジネス戦略・予測（2012-2016年）

Mobile Revenue Assurance & Fraud Management: Business Strategies & Forecasts 2012-2016
発行 Juniper Research
出版日 ページ情報 英文 157 Pages
価格
モバイル部門の収益保証・不正行為管理：ビジネス戦略・予測（2012-2016年） Mobile Revenue Assurance & Fraud Management: Business Strategies & Forecasts 2012-2016
出版日: 2012年04月01日 ページ情報: 英文 157 Pages
概要

当レポートでは、モバイル部門における収益保証（RA）・不正行為管理（FM）の動向について調査分析し、収益が損なわれる各種原因・課題、RA・FM市場の成長推進因子・阻害因子、収益確保のための各種事業戦略・ソリューション、収益漏洩のシナリオ、RA&FMシステムの導入による漏洩回避の予測、RA&FMシステム導入のライセンシング&サービス市場の予測、主要ベンダーの分析などをまとめ、概略下記の構成でお届けいたします。

エグゼクティブサマリー

第1章 モバイル収益保証&不正行為管理の概要

  • イントロダクション
  • 収益管理市場の概要
    • BSSにおけるアプリケーション区分
    • BSSトランザクションライフサイクル
  • 提起されてる問題：漏洩の脅威
    • 収益保証
    • モバイル関連の不正行為
  • 現在のモバイルエコシステムにおける課題
    • 強化されたインターネットコネクティビティ
    • スマートフォンの発展と普及
    • 次世代モバイルインタラクション
    • 横ばいの収益・CAPEXおよびOPEXの拡大

第2章 収益保証市場の進化

  • 次世代の漏洩
    • 新技術と新しい収益ストリーム
  • 段階的データ料金：ビリングにおける課題か？
  • 収益保証・不正行為管理システムの統合
    • ビジネス保証
    • 利益保証
  • 正式化されたビジネスの展望
  • 処理・ストレージの発展
    • ハードウェア
    • ソフトウェア
  • モバイルセキュリティ：4G/LTE環境におけるリスク管理
  • 産業を跨いだ協力・リセール

第3章 市場力学：収益保証の障壁と推進因子

  • 市場成長推進因子
  • 市場における障壁
  • システムのメリット

第4章 ビジネス戦略・プロセス

  • イントロダクション
    • 効果的なビジネス保証確実な提供
  • システム目標
    • 収益保証
    • 不正行為管理
  • 管理構造の最適化
    • RA/FMチームへの教育
  • ビジネスプロセスの最適化
    • 漏洩回避
    • 事後対策
  • 収益保証インフラの最適化
    • ハードウェア
    • ソフトウェア
  • 実装ソリューション
    • マネージドサービス
    • SaaS
    • コンサルタンシー

第5章 市場予測

  • イントロダクション
  • 調査手法
  • モバイルデータ市場の成長
    • オペレーターが請求するサービス収益
    • セルラーネットワークの総データトラフィック
  • 収益漏出：ワーストケースシナリオ
  • 収益漏出：ベストケースシナリオ
  • RA・FMシステムによる収益確保
  • 収益保証&不正行為管理のライセンシングとサービス

第6章 イントロダクション

  • ベンダー分析
  • Amdocs Limited
  • Connectiva Systems
  • CSG International
  • cVidya
  • HP
  • IBM
  • McAfee
  • NetCracker
  • Subex Limited
  • Syniverse
  • TEOCO Corporation
  • WeDo Technologies
  • Xintec
目次

Abstract

image1

Overview

  • 5 Year Scenario-based Forecasts
  • Extensive Breakdown of Market Dynamics
  • Exclusive Vendor Matrix for 13 Key Players

Evaluation of RA & FM Market Dynamics. This new study provides an exhaustive assessment of the next generation environment and the ways in which services, technologies and indeed, users' behaviours will impact revenue management in years to come.

In-depth Analysis of the RA & FM Ecosystem. With some 5 billion mobiles in use worldwide, MNOs must adapt in order to maintain ARPU and to battle increasing capex and opex. Readers will gain unique insight from Juniper's strategic recommendations, which will guide operators towards overcoming the challenges of a rapidly evolving environment.

New Technologies: Challenges & Opportunities for Operators. New technologies mean new revenue; but they also produce more unguarded access points for revenue leakages and more territory for fraudsters. This chapter is a must-read for operators who can learn how best to exploit advanced capabilities to drive traffic growth while simultaneously preventing fraudulent activity.

5-Year, State of the Art Forecast Suite. As the nature of network traffic and attendant revenue models diversifies, so the potential for revenue leakage increases. Juniper offers regional forecasts demonstrating the extent to which both traffic and operator-billed revenues will grow in the coming years; these then form the foundation for scenario-based forecasts for the revenue leakage that will accrue throughout the mobile network.

Readers will additionally benefit from Juniper's current and projected revenues for the size of the revenue assurance and fraud management software licensing market.

Companies Interviewed

  • CSG International
  • cVidya
  • HP
  • McAfee
  • Subex Limited
  • WeDo Technologies
  • Xintec

Vendors Profiled

  • Amdocs
  • Connectiva Systems
  • IBM
  • Netcracker
  • Syniverse
  • TEOCO

Companies Referenced

Companies Interviewed

CSG International, cVidya, HP, McAfee, Subex Limited, WeDo Technologies, Xintec

Vendors Profiled

Amdocs, Connectiva Systems, IBM, Netcracker, Syniverse, TEOCO

Companies Mentioned

Airtel, Apple, AT&T, Barclays, Billing & OSS World, Facebook, Google, Hutchinson 3G, JD Weatherspoons, JRA, Leon Restaurants, McDonald's, Microsoft, MTN, Nokia, O2, Oracle, Orange, Premier Inns, Radisson Hotels, RIM, Samsung, Starbucks, Subex, Three, T-Mobile, Vodafone, YouTube

Table of Contents

Executive Summary

Mobile Revenue Assurance & Fraud Management Overview

  • 1.1 Introduction
  • 1.2 Revenue Management Market Overview
    • 1.2.1Application Segmentation in the BSS Space
    • Figure 1.1: The Business Support System
    • i. Business Assurance
    • 1.2.2 The BSS Transactional Lifecycle
    • Figure 1.2: The Transactional Lifecycle
  • 1.3 The Problem Stated: The Threat of Leakage
    • 1.3.1 Revenue Assurance
    • Figure 1.3: Switch-to-Bill Process
    • i. Typical leakages
    • Figure 1.4: Characteristics of Revenue Leakages in the Switch-to-Bill Process
    • 1.3.2 Mobile Fraud
    • i. Fraud Types
    • Figure 1.5: A Cross-Section of Industry Fraud Terms
    • a. Subscription Fraud
    • - SIM-Cloning
    • b. Interconnect Bypass Fraud
    • - GSM Gateway Fraud
    • Figure 1.6: Legitimate Call vs Bypass Call
    • - International Call Bypass
    • - Refile
    • ii. PRS Fraud
    • iii. Roaming Fraud
    • iv. PABX (Private Area Branch Exchange) Hacking
    • v. Internal Fraud
    • vi. Dealer and Supplier Fraud
    • vii. M2M (Machine to Machine) Fraud
    • viii. Malware and SIM Hijack
  • 1.4 The Challenge of the Contemporary Mobile Eco-System
    • Figure 1.7: The Evolution of the Telecom Eco-System
    • 1.4.1 Enhanced Internet Connectivity
    • 1.4.2 The Advancement and Domination of Smartphones
    • Figure 1.8: Global Smartphone Shipment Volumes (million) over Q12010- Q42011
    • 1.4.3 Next-Generation Mobile Interaction
    • Figure 1.9: A More Demanding Consumer
    • 1.4.4 Flatlining Revenues, Rising Capex, Rising Opex
    • Figure 1.10: Base Line Analysis of Global Mobile Subscriber Growth, ARPU and Operator-Billed Service Revenues 2011-2016
    • Table 1.1: Base Line Analysis of Global Mobile Subscriber Growth, ARPU and Operator-Billed Service Revenues 2011-2016
    • Figure 1.11: The 'Nightmare' Scenario: Global MNO Service Revenues vs. Capex/Opex ($bn) 2011-2016
    • Table 1.2: The 'Nightmare' Scenario: Global MNO Service Revenues vs. Capex/Opex ($bn) 2011-2016

An Evolving Marketplace for Revenue Assurace

  • 2.1 Next-Generation Leakages
    • 2.1.1 New Technologies, New Revenue Streams
    • Figure 2.1: Total NFC Ticketing and Retail Payments Transaction Value ($m) p.a. Split by 8 Key Regions 2011-2016
    • Figure 2.2: NFC Handsets & Interim Solutions in Use (m) Split by 8 Key Regions 2011-2016
  • 2.2 Tiered Data Pricing: a Billing Headache?
    • Figure 2.3: Cell-Plan Packages
  • 2.3 Integration of Revenue Assurance and Fraud Management Systems
    • 2.3.1 Business Assurance
    • 2.3.2 Margin Assurance
  • 2.4 Formalised Business Perspective
  • 2.5 Advancements in Processing and Storage
    • 2.5.1 Hardware
    • Figure 2.4: A Typical Data Warehouse Architecture
    • i. Data Processing
    • ii. Data Storage
    • 2.5.2 Software
  • 2.6 Mobile Security: Managing Risk in a 4G/LTE Environment
  • 2.7 Cross-industry Co-operation and Re-Sale

Market Dynamics: the Hurdles & Drivers of Revenue Assurance

  • Figure 3.1: Mobile Revenue Assurance and Fraud Management Market Drivers and Hurdles
  • 3.1 Market Drivers
    • 3.1.1 Growth in Wireless Data Transaction Volume
    • Figure 3.2: Siri Voice Recognition on iPhone
    • i. Tablet devices
    • Figure 3.3: Installed Base of Tablet Devices 2011-2016 (m)
    • 3.1.2 Regulation
    • i. Addressing roaming-based Bill Shock
    • a. Case Study: European Union (EU) Regulation
    • ii. NRTRDE (Near-Real Time Roaming Data Exchange)
    • 3.1.3 Real-Time Charging and Policy: Self-Service
  • 3.2 Market Hurdles
    • 3.2.1 Regulatory Compliance
    • i. Sarbanes-Oxley (SOX) Act
    • ii. European Union Data Retention Directive (Directive 2006/24/EC)
    • iii. EU Data Protection Directive
    • iv. Cloud Networks and Compliance Difficulties
    • 3.2.2 The Operational Responsibility Gap
    • i. Cross-Organisation
    • ii. Intra-Organisation
    • 3.2.3 Lack of Cross-department Collaboration
    • 3.2.4 Poor Visibility of Extended Revenue Chain
    • 3.2.5 Upsurge in Third Party Involvement
    • 3.2.6 Lack of Prioritisation in the Business Model
    • i. Tier 2/3 Mobile Network Operators
    • 3.2.7 Lack of Skilled Professionals
    • 3.2.8 Subjectivity, Consistency and Integrity of Intelligence
    • 3.2.9 High Data Volume
    • 3.2.10 High TCO (Total Cost of Ownership)
    • 3.2.11 Limited Root-cause Analysis and Real-Time Capabilities
    • 3.2.12 Need for Technology Agnostic Solutions
  • 3.3 System Benefits
    • Figure 3.4: The Benefits of Revenue Assurance/Fraud Management Systems

Business Strategies and Processes

  • 4.1 Introduction
    • Figure 4.1: Business Model
    • 4.1.1 Ensuring Effective Business Assurance
  • 4.2 System Objectives
    • 4.2.1 Revenue Assurance
    • 4.2.2 Fraud Management
  • 4.3 Optimising the Administrative Structure
    • 4.3.1 Educating the RA/FM Teams
  • 4.4 Optimising the Business Processes
    • Figure 4.2: The Business Process
    • 4.4.1 Leakage Prevention
    • i. Revenue Assurance
    • ii. Fraud Management
    • 4.4.2 Reactive Processes
  • 4.5 Optimising Infrastructure for Revenue Assurance
    • 4.5.1 Hardware
    • 4.5.2 Software
    • i. Interface
    • Figure 4.3: Examples of a Dashboard
    • Figure: 4.4 Example of a Subscription Fraud Match Report
  • 4.6 Implementation Solutions
    • 4.6.1 Managed Services
    • 4.6.2 SaaS (Software as Service)
    • i. Cloud-delivery model
    • 4.6.3 Consultancy

Market Forecasts

  • 5.1 Introduction
  • 5.2 Methodology
    • 5.2.1 Geographical Splits
    • 5.2.2 Methodology and Assumptions
    • Figure 5.1: Methodology for Determining the Value of Revenue Assurance & Fraud Management
  • 5.3 Growth of Mobile Data Market
    • 5.3.1 Operator-Billed Service Revenues
    • Figure 5.2: Total Operator-Billed Services Revenues ($bn) Split by 8 Key Regions 2011-2016
    • Table 5.1: Total Operator-Billed Services Revenues ($bn) Split by 8 Key Regions 2011-2016
    • i. Operator-Billed Voice Revenues
    • Figure 5.3: Total Operator-Billed Voice Revenues ($bn) Split by 8 Key Regions 2011-2016
    • Table 5.2: Total Operator-Billed Voice Revenues ($bn) Split by 8 Key Regions 2011-2016
    • ii. Operator-Billed Data Revenues
    • Figure 5.4: Total Operator-Billed Data Revenues ($bn) Split by 8 Key Regions 2011-2016
    • Table 5.3: Total Operator-Billed Data Revenues ($bn) Split by 8 Key Regions 2011-2016
    • 5.3.2 Total Data Traffic through the Cellular Network
    • Figure 5.5: Total Data Traffic through the Cellular Network (PB/Annum) Split by 8 Key Regions 2011-2016
    • Table 5.4: Total Data Traffic through the Cellular Network (PB/Annum) Split by 8 Key Regions 2011-2016
  • 5.4 Revenue Leakage: Worst-case Scenario
    • Figure 5.6: Total Operator-Billed Revenue Leakage (%), Worst-case Scenario 2011-2016
    • Table 5.5: Total Operator-Billed Revenue Leakage (%), Worst-case Scenario 2011-2016
    • Figure 5.7: Global Revenue Leakage ($bn) from Operator-Billed Services, Worst-case Scenario Split by 8 Key Regions 2011-2016
    • Table 5.6: Global Revenue Leakage ($bn) from Operator-Billed Services, Worst-case Scenario Split by 8 Key Regions 2011-2016
  • 5.5 Revenue Leakage: Best-Case Scenario
    • Figure 5.8: Total Operator-Billed Revenue Leakage (%), Best-case Scenario Split by 8 Key Regions 2011-2016
    • Table 5.7: Total Operator-Billed Revenue Leakage (%) Best-case Scenario Split by 8 Key Regions 2011-2016
    • Figure 5.9: Total Operator-Billed Revenue Leakage ($bn), Best-case Scenario Split by 8 Key Regions 2011-2016
    • Table 5.8: Total Operator-Billed Revenue Leakage ($bn), Best-case Scenario Split by 8 Key Regions 2011-2016
  • 5.6 Revenue Savings Accrued by RA and FM Systems
    • Figure 5.10: Revenue Leakage by Scenario (Sbn) 2011-2016
    • Table 5.9: Revenue Leakage by Scenario and Implied Annual/Cumulative Leakage Reduction under Best-case Scenario ($bn) 2011-2016
  • 5.7 Revenue Assurance & Fraud Management Licensing and Services
    • Figure 5.11: Value of the RA and FM Software Licensing & Services ($m) Split by 8 Key Regions 2011-2016
    • Table 5.10: Value of RA and FM Software Licensing & Services ($m) Split by 8 Key Regions 2011-2016

Vendor Strategies

  • Executive Summary
    • ES1 Mobile Revenue Assurance and Fraud Defined
    • ES2 Revenue Management Market Overview
    • ES3 Market Projections
    • ES4 Conclusions and Strategic Recommendations
    • Mobile Revenue Assurance & Fraud Management Overview
  • 1.1 Introduction
  • 1.2 Revenue Management Market Overview
    • 1.2.1Application Segmentation in the BSS Space
    • Figure 1.1: The Business Support System
    • i. Business Assurance
    • 1.2.2 The BSS Transactional Lifecycle
    • Figure 1.2: The Transactional Lifecycle
  • 1.3 The Problem Stated: The Threat of Leakage
    • 1.3.1 Revenue Assurance
    • Figure 1.3: Switch-to-Bill Process
    • i. Typical leakages
    • Figure 1.4: Characteristics of Revenue Leakages in the Switch-to-Bill Process
    • 1.3.2 Mobile Fraud
    • i. Fraud Types
    • Figure 1.5: A Cross-Section of Industry Fraud Terms
    • a. Subscription Fraud
    • - SIM-Cloning
    • b. Interconnect Bypass Fraud
    • - GSM Gateway Fraud
    • Figure 1.6: Legitimate Call vs Bypass Call
    • - International Call Bypass
    • - Refile
    • ii. PRS Fraud
    • iii. Roaming Fraud
    • iv. PABX (Private Area Branch Exchange) Hacking
    • v. Internal Fraud
    • vi. Dealer and Supplier Fraud
    • vii. M2M (Machine to Machine) Fraud
    • viii. Malware and SIM Hijack
  • 1.4 The Challenge of the Contemporary Mobile Eco-System
    • Figure 1.7: The Evolution of the Telecom Eco-System
    • 1.4.1 Enhanced Internet Connectivity
    • 1.4.2 The Advancement and Domination of Smartphones
    • Figure 1.8: Global Smartphone Shipment Volumes (million) over Q12010- Q42011
    • 1.4.3 Next-Generation Mobile Interaction
    • Figure 1.9: A More Demanding Consumer
    • 1.4.4 Flatlining Revenues, Rising Capex, Rising Opex
    • Figure 1.10: Base Line Analysis of Global Mobile Subscriber Growth, ARPU and Operator-Billed Service Revenues 2011-2016
    • Table 1.1: Base Line Analysis of Global Mobile Subscriber Growth, ARPU and Operator-Billed Service Revenues 2011-2016
    • Figure 1.11: The 'Nightmare' Scenario: Global MNO Service Revenues vs. Capex/Opex ($bn) 2011-2016
    • Table 1.2: The 'Nightmare' Scenario: Global MNO Service Revenues vs. Capex/Opex ($bn) 2011-2016
    • An Evolving Marketplace for Revenue Assurace
  • 2.1 Next-Generation Leakages
    • 2.1.1 New Technologies, New Revenue Streams
    • Figure 2.1: Total NFC Ticketing and Retail Payments Transaction Value ($m) p.a. Split by 8 Key Regions 2011-2016
    • Figure 2.2: NFC Handsets & Interim Solutions in Use (m) Split by 8 Key Regions 2011-2016
  • 2.2 Tiered Data Pricing: a Billing Headache?
    • Figure 2.3: Cell-Plan Packages
  • 2.3 Integration of Revenue Assurance and Fraud Management Systems
    • 2.3.1 Business Assurance
    • 2.3.2 Margin Assurance
  • 2.4 Formalised Business Perspective
  • 2.5 Advancements in Processing and Storage
    • 2.5.1 Hardware
    • Figure 2.4: A Typical Data Warehouse Architecture
    • i. Data Processing
    • ii. Data Storage
    • 2.5.2 Software
  • 2.6 Mobile Security: Managing Risk in a 4G/LTE Environment
  • 2.7 Cross-industry Co-operation and Re-Sale
    • Market Dynamics: the Hurdles & Drivers of Revenue Assurance
    • Figure 3.1: Mobile Revenue Assurance and Fraud Management Market Drivers and Hurdles
  • 3.1 Market Drivers
    • 3.1.1 Growth in Wireless Data Transaction Volume
    • Figure 3.2: Siri Voice Recognition on iPhone
    • i. Tablet devices
    • Figure 3.3: Installed Base of Tablet Devices 2011-2016 (m)
    • 3.1.2 Regulation
    • i. Addressing roaming-based Bill Shock
    • a. Case Study: European Union (EU) Regulation
    • ii. NRTRDE (Near-Real Time Roaming Data Exchange)
    • 3.1.3 Real-Time Charging and Policy: Self-Service
  • 3.2 Market Hurdles
    • 3.2.1 Regulatory Compliance
    • i. Sarbanes-Oxley (SOX) Act
    • ii. European Union Data Retention Directive (Directive 2006/24/EC)
    • iii. EU Data Protection Directive
    • iv. Cloud Networks and Compliance Difficulties
    • 3.2.2 The Operational Responsibility Gap
    • i. Cross-Organisation
    • ii. Intra-Organisation
    • 3.2.3 Lack of Cross-department Collaboration
    • 3.2.4 Poor Visibility of Extended Revenue Chain
    • 3.2.5 Upsurge in Third Party Involvement
    • 3.2.6 Lack of Prioritisation in the Business Model
    • i. Tier 2/3 Mobile Network Operators
    • 3.2.7 Lack of Skilled Professionals
    • 3.2.8 Subjectivity, Consistency and Integrity of Intelligence
    • 3.2.9 High Data Volume
    • 3.2.10 High TCO (Total Cost of Ownership)
    • 3.2.11 Limited Root-cause Analysis and Real-Time Capabilities
    • 3.2.12 Need for Technology Agnostic Solutions
    • 3.3 System Benefits
    • Figure 3.4: The Benefits of Revenue Assurance/Fraud Management Systems
    • Business Strategies and Processes
  • 4.1 Introduction
    • Figure 4.1: Business Model
    • 4.1.1 Ensuring Effective Business Assurance
  • 4.2 System Objectives
    • 4.2.1 Revenue Assurance
    • 4.2.2 Fraud Management
  • 4.3 Optimising the Administrative Structure
    • 4.3.1 Educating the RA/FM Teams
  • 4.4 Optimising the Business Processes
    • Figure 4.2: The Business Process
    • 4.4.1 Leakage Prevention
    • i. Revenue Assurance
    • ii. Fraud Management
    • 4.4.2 Reactive Processes
  • 4.5 Optimising Infrastructure for Revenue Assurance
    • 4.5.1 Hardware
    • 4.5.2 Software
    • i. Interface
    • Figure 4.3: Examples of a Dashboard
    • Figure: 4.4 Example of a Subscription Fraud Match Report
  • 4.6 Implementation Solutions
    • 4.6.1 Managed Services
    • 4.6.2 SaaS (Software as Service)
    • i. Cloud-delivery model
    • 4.6.3 Consultancy
    • Market Forecasts
  • 5.1 Introduction
  • 5.2 Methodology
    • 5.2.1 Geographical Splits
    • 5.2.2 Methodology and Assumptions
    • Figure 5.1: Methodology for Determining the Value of Revenue Assurance & Fraud Management
  • 5.3 Growth of Mobile Data Market
    • 5.3.1 Operator-Billed Service Revenues
    • Figure 5.2: Total Operator-Billed Services Revenues ($bn) Split by 8 Key Regions 2011-2016
    • Table 5.1: Total Operator-Billed Services Revenues ($bn) Split by 8 Key Regions 2011-2016
    • i. Operator-Billed Voice Revenues
    • Figure 5.3: Total Operator-Billed Voice Revenues ($bn) Split by 8 Key Regions 2011-2016
    • Table 5.2: Total Operator-Billed Voice Revenues ($bn) Split by 8 Key Regions 2011-2016
    • ii. Operator-Billed Data Revenues
    • Figure 5.4: Total Operator-Billed Data Revenues ($bn) Split by 8 Key Regions 2011-2016
    • Table 5.3: Total Operator-Billed Data Revenues ($bn) Split by 8 Key Regions 2011-2016
    • 5.3.2 Total Data Traffic through the Cellular Network
    • Figure 5.5: Total Data Traffic through the Cellular Network (PB/Annum) Split by 8 Key Regions 2011-2016
    • Table 5.4: Total Data Traffic through the Cellular Network (PB/Annum) Split by 8 Key Regions 2011-2016
  • 5.4 Revenue Leakage: Worst-case Scenario
    • Figure 5.6: Total Operator-Billed Revenue Leakage (%), Worst-case Scenario 2011-2016
    • Table 5.5: Total Operator-Billed Revenue Leakage (%), Worst-case Scenario 2011-2016
    • Figure 5.7: Global Revenue Leakage ($bn) from Operator-Billed Services, Worst-case Scenario Split by 8 Key Regions 2011-2016
    • Table 5.6: Global Revenue Leakage ($bn) from Operator-Billed Services, Worst-case Scenario Split by 8 Key Regions 2011-2016
  • 5.5 Revenue Leakage: Best-Case Scenario
    • Figure 5.8: Total Operator-Billed Revenue Leakage (%), Best-case Scenario Split by 8 Key Regions 2011-2016
    • Table 5.7: Total Operator-Billed Revenue Leakage (%) Best-case Scenario Split by 8 Key Regions 2011-2016
    • Figure 5.9: Total Operator-Billed Revenue Leakage ($bn), Best-case Scenario Split by 8 Key Regions 2011-2016
    • Table 5.8: Total Operator-Billed Revenue Leakage ($bn), Best-case Scenario Split by 8 Key Regions 2011-2016
  • 5.6 Revenue Savings Accrued by RA and FM Systems
    • Figure 5.10: Revenue Leakage by Scenario (Sbn) 2011-2016
    • Table 5.9: Revenue Leakage by Scenario and Implied Annual/Cumulative Leakage Reduction under Best-case Scenario ($bn) 2011-2016
  • 5.7 Revenue Assurance & Fraud Management Licensing and Services
    • Figure 5.11: Value of the RA and FM Software Licensing & Services ($m) Split by 8 Key Regions 2011-2016
    • Table 5.10: Value of RA and FM Software Licensing & Services ($m) Split by 8 Key Regions 2011-2016
    • Vendor Strategies
  • 6.1 Introduction
  • 6.2 Vendor Analysis
    • 6.2.1 Vendor Assessment Methodology
    • Table 6.1: Vendor Capability Assessment Criteria
    • 6.2.2 Limitations and Interpretation
    • 6.2.3 Positioning Matrix Results
    • Figure 6.1: Mobile RA and Fraud Management Vendor Positioning Matrix
    • 6.2.4 Vendor Groupings
    • i. Summary
    • ii. On Track Vendors
    • iii. Exceeding Expectations Vendors
    • iv. Further Potential Vendors
    • 6.2.5 Strategy Conclusions - Corporate Activity
  • 6.3 Amdocs Limited
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.4 Connectiva Systems
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.5 CSG International
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.6 cVidya
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • Figure 6.2: cVidya Solution
    • iv. Products and Services
    • Figure 6.3: cVidya Iris - Integrated Revenue Intelligence Solution Portfolio
    • Figure 6.4: cVidya MoneyMap Solution
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.7 HP
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.8 IBM
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.9 McAfee
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.10 NetCracker
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.11 Subex Limited
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • Figure 6.5: Subex's Business Optimisation Solution
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.12 Syniverse
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.13 TEOCO Corporation
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • - Revenue Assurance
    • - Customer Assurance
    • - Margin Assurance
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.14 WeDo Technologies
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • Figure 6.6: RAID: FMS Approach
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities
  • 6.15 Xintec
    • i. Corporate Profile
    • ii. Geographic Spread
    • iii. Key Clients & Strategic Partnerships
    • iv. Products and Services
    • Figure 6.7: FMSlite Infrastructure
    • v. Juniper's View: Key Strengths and Strategic Development Opportunities

「モバイル部門の収益保証・不正行為管理：ビジネス戦略・予測（2012-2016年）」は2012年04月01日にジュニパーリサーチより発行されました。 当レポートは157 Pagesで構成され、税抜￥284,267より販売しています。
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