Table of Contents
| Chapter 1. Executive Summary (12 pages) |  |
| Chapter 2. International Revenue Share (34 pages) | |
| A. How IRSF Predators are Evolving their Fraud Attacks | |
| – Predators in Nature vs. Telecom | |
| – The PRISM IPRN Test Number Database | |
| – Big Increase in IPRN Numbers and Aggregators | |
| – Why Fraudsters are Shifting IRSF to New Destinations | |
| – Fraudsters Target Valid Non-VAS & MSRN Numbers | |
| – Number Misappropriation or Number Hijacking | |
| – Legal Remedies for Controlling IPRN Aggregators? | |
| – Why Least Cost Routing is Causing Fraud to Spread | |
| – The Value of Trusted Networks | |
| – The i3 Forum Code of Conduct | |
| – Global Assessment of Fraud Management Practices | |
| – Tactics and Automation of the Fraudsters | |
| B. Machine Learning, Analytic Scans & Tailored Treatment | |
| – A Machine Learning View of Analytics | |
| – Mobileum Developing Full-Scale Fraud System | |
| – Profiling Traffic to Deliver Finer Grain Analytics | |
| – Deeper Traffic Knowledge Allows Better Treatment | |
| – Deep Analysis of Number Ranges | |
| – Mobileum Automates the Traffic Treatment | |
| – Better Accuracy and Less Chasing False Positives | |
| – An Advanced Diagnostics Tool for IRSF Fraud | |
| C. Protecting 900+ Global MVNOs from IRSF Fraud | |
| – Why IRSF Fraudsters are Targeting MVNOs | |
| – Light vs. Full MVNOs | |
| – Scarce Fraud Manager Attention at MVNOs | |
| – A Five-Point Plan for MVNO Protection | |
| – Consulting MVNOs on Fraud Concerns | |
| D. IRSF: Are We Winning Against Telecom Pirates? | |
| – IRSF – A History on the Threat’s Evolution | |
| – Tech Advancements Led to More Fraud Attack Avenues | |
| – The Roaming Gateway to IRSF | |
| – Why Certain Countries are IRSF Destinations | |
| – Bound by International Agreements | |
| – Impact of IRSF on all-IP networks and LTE | |
| – Industry Cooperation | |
| – The Special Case of the Pacific Islands | |
| – IRSF: Mobile Roaming Scenario | |
| – How Fraudsters Advertise Themselves | |
| – The IRSF Number Providers | |
| – Why It’s Hard to Detect and Reconstruct IRSF Cases | |
| – Consulting in the Fraud Business | |
| – A Shared Fraud Managment Model | |
| – Legislation to Stop the Fraud Money Flow | |
| Chapter 3. Mobile Roaming & SMS Fraud (23 pages) | |
| A. Safety in Numbers and NRTRDE: Syniverse's Fraud Intelligence | |
| – The Power of Safety in Numbers in Fraud Control | |
| – Why Fraudsters Love Roaming: The Value NRTRDE | |
| – Syniverse's Global Fraud Footprint | |
| – Details on the Intercarrier Process behind NRTRDE | |
| – Intercarrier Data Handoffs & GDPR Requirements | |
| – Global Fraud Practices & Law Enforcement's Role | |
| B. A2P Bypass: Arraxe Fights Schemes to Exploit Roam-Like-at-Home | |
| – Why Telecom's Darwinian Struggle Invites Fraud | |
| – The A2P SMS Revenue Bright Spot | |
| – How Fraudsters Play the A2P Game | |
| – Fraudsters Exploiting Roam-Like-at-Home | |
| – How Araxxe Combats SMS Fraud | |
| C. Protecting the Roaming Cash Cow: Global Testing of Advanced Networks | |
| – Overview of SIGOS Roaming Assurance | |
| – Tapping into a Global Roaming Test Platform | |
| – Many Roaming Processes Need to be Tested | |
| – Roaming Testing when Mobile Network Changes Occur | |
| – Financial Impact of Regulations on Roaming in Europe | |
| – The Huge Potential of Silent Roamers | |
| D. iconectiv's Fraud & Identity Solutions in Bypass & A2P Messaging | |
| – iconectiv's Revenue Assurance Business | |
| – The SIM Box Problem in A2P SMS Bypass | |
| – Nuances in the A2P Business | |
| – Operators Lack Control over A2P Termination | |
| – Why a Managed Service is Key to A2P Fraud Protection | |
| – Selection of the Right SMS Aggregators is Essential | |
| Chapter 4. Enterprise PBX Protection (23 pages) | |
| A. History of PBX Hijacking and Relations between Enterprises & Telcos | |
| – The History of Enterprise PBX Hijacking | |
| – Early Years: Phone Booth Calls from New York City | |
| – Ramping Down Weekday Fraud to Avoid Detection | |
| – Fraud Responsibility after Enterprises Bought Their Own PBXs | |
| – Why Operators Cannot Refuse IRSF Payments | |
| – Fraud Insurance Plans are Rare | |
| B. Oculeus Launches IRSF Cloud Defense-in-Depth for Enterprises | |
| – PBX Fraud Blocking is Now a Global Cloud Service | |
| – Set Up of the Managed Service via Central Registration | |
| – Almost Zero Administration & PBX Remains Secure | |
| – What Kind of Enterprises Need the Service? | |
| – How SIP IP has Opened Pandora's Box | |
| – Enterprises Want Great Control of Telecom Assets | |
| – Operators to Act as Distributors of Oculeus-Protect | |
| – Older Generation Signaling Also Supported | |
| C. PC Software that Blocks Telecom Fraud at the Enterprise PBX | |
| – Callista Group's PBX Blocking via PC Software | |
| – Genesis of the Control Phreak Product | |
| – Worst Case of Enterprise IRSF Fraud Seen | |
| – What Intelligence are Phreakers Looking? | |
| – Ingenious Ways Hackers Discover Weak Passwords | |
| – The Problem with Four Digit Passcodes | |
| – How Phreakers Work with Fraudsters | |
| – Fraudsters Hiding their Tracks by Chaining PBXs | |
| – How Control Phreak Works | |
| – Cost for Enterprise Protection | |
| – PXX Manufacturers Who Cooperate with Callista | |
| D. Automatic Fraud Blocking at the Enterprise PBX | |
| – Will Fraudster Play the Long Game in IRSF? | |
| – A Solution to Block Fraud at Enterprise PBX | |
| – System Under Development to Guard the PBX | |
| – A 100% Self-Maintained System | |
| – The Forensic vs. Network Side of Fraud Control | |
| – Anomaly Detection Today, Machine Learning Future | |
| – Many Sources of PBX Fraud | |
| – Oculeus Philosophy on Software Development | |
| Chapter 5. SIM Box Bypass Fraud (43 pages) | |
| A. LATRO Teams Up with Law Enforcement to Seize SIM Boxes | |
| – Three Systems Required to Curb SIM Box Bypass | |
| – Success in Geo-Locating SIM Boxes | |
| – Financial Impact of SIM Box Raids | |
| – Network Visualization of SIM Boxes | |
| – LATRO's Signaling Expertise | |
| – LATRO to Offer a Combined RA/FM Solution | |
| – Signaling to Billing Analytics | |
| – LATRO Develops an Expertise in IoT Analytics | |
| B. The Art of Deception and Analysis in SIM Box Bypass | |
| – Why Test Call Generators are Vital in Bypass Control | |
| – White List Defensive Tool | |
| – Making Test Calls to Genuine Subscribers | |
| – Why Using a Large White List is So Valuable | |
| – Interconnect Pricing as Measure of SIM Box Fraud Control | |
| – Reading the Pulse of SIM Box Fraud in a Country | |
| C. Stealth Test Calls: SIGOS Technique to Block SIM Box Bypass | |
| – The SIGOS Fraud Business | |
| – Optimized CDR Profiling for the SIM Box Bypass Problem | |
| – Regulators are Now Very Active in the SIM Box Fight | |
| – Three Reasons why Classical SIM Box Detection is Hard | |
| – SIGOS' Stealth Test Call Technology | |
| – Success of Stealth Mode in Many Countries | |
| – How Operator Supports the Stealth Mode | |
| – Key Advantages of the Stealth Mode | |
| – Why Stopping SIM Box Bypass is a High Challenge | |
| D. Outgoing SIM Box Bypass & Spikes in CLI-Tampering | |
| – Understanding the Psychology of the Fraudster | |
| – Outgoing SIM Box Fraud Example | |
| – A No-Revenue-Loss Kind of Fraud | |
| – Fraudulent CLI Re-Filing in Europe | |
| – Several Operators in the CLI Refiling Chain | |
| – Technical Platform Less Critical than Analyst | |
| E. Integrated Test Call & CDR Analysis in SIM Box and OTT Bypass Fraud | |
| – Combining FMS CDR Analysis and Test Calls | |
| – The SIGOS Acquisition of Meucci Solutions | |
| – Brief History of SIM Box Bypass Fraud | |
| – Bypass Detection via the Largest Test Call Network | |
| – Investing in Counter-Measures to Avoid Detection | |
| – A Cocktail of Medicines to Cure Bypass Disease | |
| – The Emergence of VIBER Bypass | |
| F. How a Global Robot Network Detects Voice and SMS Bypass | |
| – Why Bypass Fraud is Hard to Detect | |
| – The Araxxe Robot Network | |
| – The Root Causes of SIM Box Bypass Fraud | |
| – How Bypass Fraudsters Exploit Interconnect Paths | |
| – Coordinating FMS and Test Call Generation | |
| – Efficient Algorithms in Bypass Test Calls are Key | |
| – Strange Events in the SIM Box Bypass World | |
| – A Growing Number of Fraud Schemes in A2P SMS | |
| G. Test Call Generators: Their Use in Mobile Billing Assurance | |
| – Active Call Generation vs. Passive Revenue Assurance | |
| – The Value of a Test Calls in RA | |
| – Roaming Assurance and Global Coverage | |
| – How Operators Work with a TCG Vendor | |
| – The Complexity of Re-Rating Calls | |
| – Demand for Assuring Non-Recurring Charges | |
| – Regulators Monitor Local Operators for Overcharges | |
| – End-to-Testing vs. Over-the-Air Call Simulation | |
| – Quality KPIs Used to Calculate Bonuses | |
| H. Network Protocol Analysis in SIM Box Fraud | |
| – The Hotbeds of SIM Box Bypass | |
| – Why SIM Box Operations Run in Urban Areas | |
| – SIM Box Detection Technologies | |
| – The Correlation between Revenue Loss & SIM Box Bypass | |
| – Confiscating Equipment & Arresting Fraudsters | |
| Chapter 6. Insider, Dealer & Sales Fraud (22 pages) | |
| A. Insider Data Theft & Fraud: Veriato Monitors the Fraud Endpoints | |
| – Why Insider Threat Management Needs More Attention | |
| – On the Network vs. On the Endpoint | |
| – Why Machine Learning is Essential | |
| – Advice from the 2019 Insider Threat Maturity Report | |
| – Departments Who Need Access to Sensitive Monitoring Data | |
| – Coverage for Desktops and Android Cellphones | |
| – Combining User Activity Monitoring & Machine Learning | |
| B. Verizon Insider Threat Report — Summary of Key Findings | |
| – New Title | |
| – Summary Research Findings | |
| – The Five Types of Insider Data Breach Threats | |
| – Scenario 1: Insider Agent Working on Behalf of Outside Entity | |
| – Scenario 2: Data Collector Embedded in System Firmware | |
| – The People and Asset Elements of the Insider Threat | |
| – The Importance of Coordination Among Stakeholders | |
| – Eleven Threat Countermeasures | |
| – Making Full Use of the Verizon Report | |
| C. Create an Anti-Fraud Culture in Your Telecom Organization | |
| – Insider Fraud is a Massive Telecom Problem | |
| – Is There a Fraud Culture at Your Company? | |
| – Different Country Attitudes Toward Fraud | |
| – Insider Fraud Happens at All Department Levels | |
| – Screening the People Responsible for Fighting Fraud | |
| – Procedures to Put in Place to Fight Fraud | |
| – Preparation Around the Evidence to be Collected | |
| – Senior Management's Role | |
| – Consistency in the Anti-Fraud Program | |
| D. Detecting Criminal Activity in the Sales Process | |
| – Focus of Investigation: Systems Related to Sales | |
| – A Multi-Million Dollar Horror Story in Sales | |
| – Enabling Investigators to Detect Abnormal Activities | |
| – Fraud in the Dealer Change: An Example | |
| – Verifying the Salesperson's Activity | |
| – Give the Investigator as Much Info as Possible | |
| – The Fraud Challenge in Offices & Dealer Stores | |
| Chapter 7. Cross Industry Fraud, IoT, & Identity Solutions (32 pages) | |
| A. NuData Sheds Light on Identity in a Fraud-Ridden World | |
| – Verifying Identity through Digital Behavior | |
| – Verifiying via Multiple Factors of Interaction | |
| – Defining Digital Behavior | |
| – The NuData System of Digital Behavior Analysis | |
| – NuData's Experience in the Business | |
| – International Differences | |
| – US Market is Strong in eTail Protection | |
| – NuData Services Offered Through Mastercard | |
| – 50% Protection & 50% Optimization & Retention | |
| B. Syniverse's Secure Global Access: A Neutral Third Party IoT Service | |
| – Why Digital Giants Have Delayed IoT Investment | |
| – The GRX Private IPX Network | |
| – High Security for the Largest IPX in the World | |
| – Daily Petabyte Consumption on the IPX | |
| – A Big Efficiency Play for Global Wireless Net | |
| – Secure Global Access for IoT | |
| – Supporting 50,000 Unique Non-Human Devices | |
| – Monitoring the Non-Human Use Cases in IoT | |
| – RCS Multimedia to Replace A2P Messaging | |
| C. WeDo Explores the IoT Ecosystem in Search of Tomorrow's Pivotal Fraud & Business Assurance Solutions | |
| – The New Product Development Challenge | |
| – When Telcos Don't Control the Data of IoT Devices | |
| – The Challenge of Acquiring Domain Knowledge | |
| – Provisioning a Service in a Connected Car | |
| – Fraud and Revenue Assurance Challenges in IoT | |
| – Many Different Slices of IoT QoS in a | |
| – How WeDo Gained Experience in IoT Ecosystem | |
| – The Importance of Edge Computing in IoT | |
| D. Device Intelligence: Guarding Consumer Access Points from Fraudsters | |
| – Fraud Protection & Customer Experience Sensitive | |
| – Experian's Business | |
| – Stopping Identity Theft | |
| – Credit Mules | |
| – Collecting Device Intelligence | |
| – Assuming Identity is Compromised | |
| E. BT Americas: Why Security is a Major Board Room Concern | |
| – BT America's Security Practice | |
| – BT is the Sixth Largest Data Mover | |
| – Large Global Practice in Security Managed Services | |
| – Six Motivators of Data Security Protection | |
| – What a Security Assessment is About | |
| F. Cross-Industry "Know Your Customer" Biometrics to Verify Identity | |
| – The FRS Labs Business | |
| – Identity Verification in India | |
| – The Indian Government's UIDAI Identity Program | |
| – Know Your Customer and Verify Identity | |
| – Opportunities to Exploit the National Database | |
| – Facial Identification | |
| – Storing Facial Profiles Without Violating Privacy | |
| – Anti-Spoofing Measures for the Camera | |
| – Telecoms Must Buy Cross-Industry Solutions | |
| Chapter 8. The Fraud Control Role of Regulators & Law Enforcement (13 pages) | |
| A. Tracfone's Fraud Controls & Law Enforcement Actions to Stop Cell Phone Trafficking | |
| – Tracfone and the US Mobile Market | |
| – Tracfone: An Impressive MVNO and Retailer Partner | |
| – Excellent Subscriber per Employee Efficiency | |
| – A Simple IRSF Control Measure using 800 Numbers | |
| – Cellphone Trafficking: A Financial Burden & Deadly Game | |
| – TracFone’s Aggressive Law Enforcement Campaign | |
| – Conclusion | |
| B. Regulator Action to Stop SIM Box Damage to Developing Nations | |
| – The Costs of SIM Box Bypass Fraud to a Nation | |
| – Breakdown of 7 National Problems due to Bypass Fraud | |
| – How SIM Box Servers have Magnified the Bypass Problem | |
| – Why Regulators Must Step up Law Enforcement | |
| – Four Key Steps Regulators Must Take | |
| Chapter 9. Databases in Telecom Fraud (15 pages) | |
| A. The Early Warning Power of IPRN Test Call Detection | |
| – The Importance of IPRN Monitoring in IRSF | |
| – How IPRN Data Sets Up a Fraud Attack | |
| – The Flow of Criminal Operations in IRSF | |
| – IPRN Providers & Their Rate Cards | |
| – An Early Warning Database for IPRN Numbers | |
| – Customers Finding the IPRN Database Useful | |
| – Accessing the PRISM Database | |
| B. Bringing Telecom Reference Data to Fraud Management | |
| – Marrying Digital Tech with "Baroque" Tech | |
| – History of Biaas in Telecom Reference Data | |
| – A New Database Specific to IRSF Fraud Protection | |
| – Tracking Unallocated Numbers | |
| – Accurate List of Higher Tariff Destination Number Ranges | |
| – Pricing for the Fraud Number Database | |
| – Working with Fraud Control Solution Vendors | |
| Chapter 10. Wholesaler Fraud Strategies (32 pages) | |
| A. Coping with Chaos: The Copernican Revolution in Wholesale | |
| – Planning for Unpredictability in Wholesale | |
| – Wholesale Margins have Vaporized | |
| – Manual Gives Way to Automated Wholesale Ops | |
| – Price Pressure and Job Losses | |
| – Who Wins in Wholesale Traffic Routing? | |
| – The Retail Transition to Digital Services over Voice | |
| – Who Wins the Consolidation Game? | |
| – Strategies Wholesalers Use to Win Over Retailers | |
| – Helping Retailers Work with Wholesalers | |
| B. PCCW Global: First Tier 1 Carrier to Deliver SDN Connectivity as a Worldwide Enterprise Service | |
| – Software Define Networks are a Provisioning Innovation | |
| – PCCW, a Tier 1 Global IP Provider | |
| – The Console Connect Fast Connection | |
| – From Manual to Fully Automated Provisioning of Data Circuits | |
| – Enterprise Customers Provisioning Their Own Circuits | |
| – The LinkedIn-Like Console Connect Interface | |
| – How Fast-Connection Changes Wholesale | |
| – Telecom Moves to Software that Enables Customer Agility | |
| C. Wholesaler Fraud Prevention Strategies: Tata Communications | |
| – Tata Communication's Business | |
| – Taking the Fraud Concerns of Retails Head On | |
| – Making the Organization More Accountable | |
| – Doing Due Diligence on Suppliers | |
| – Recognizing the Red Flags of Questionable Suppliers | |
| – Steps Tata Communications Takes to Protect Customers | |
| – Identifying Number Ranges that are a Fraud Risk | |
| – Final Advice to Carriers | |
| D. iBasis Automates Wholesaler Protection of Retail Carriers | |
| – Telecom Price Competition puts the Emphasis on Fraud Protection | |
| – iBasis Protects Large and Small Providers | |
| – Blocking Fraud, but Keeping Retail Customer in Control | |
| – Two Forms of Controlling Fraud Disconnects | |
| – Benefits of Wholesaler Fraud Blocking | |
| – iBasis's Sophisticated Fraud Capability | |
| E. Fraud Management Collaboration: Real Intelligence Sharing | |
| – Cross-Operator Software & Processes | |
| – The BICS FraudGuard Protection Program | |
| – How Operators Help Each Other Through FraudGuard | |
| – The Global Fraud Intelligence of a Large Transit Carrier | |
| – Small Operators are Often Vulnerable to Fraud | |
| – Roll out of FraudGuard | |
| – FraudGuard is Also Valuable for Fraud-Mature Operators | |
| F. The Retail Operator Case for Anti-Fraud Protection from Wholesalers | |
| – Being Protective of Your OpCos and Partners | |
| – The Lack of Fraud Resources at Small Operators | |
| – Wholesalers Need to Take on the Responsibility | |
| – Problems When a Nation's Number Ranges are Blocked | |
| – Whoilesaler Deep Commitment to Retailers is Central | |
| – Consulting with Operators about Fraud | |
| – Why Retail Operators Should be Firm with Wholesalers | |
| Chapter 11. VoIP and Cloud Provider Fraud Control (19 pages) | |
| A. Cloud Player Evolve IP: Layered Defense to Control Fraud | |
| – Telecom/IP Player's View of Fraud Control | |
| – The Unique Evolve-IP Business Model | |
| – The Strategy: Cloud Play for Enterprises | |
| – A Layered Defense: Multiple Fraud Solutions | |
| – Fraud Alerting Before Call Closes | |
| – Fraud Management Staffing | |
| – The Network Engineering Operation | |
| – Customers Served & Market Positioning | |
| – Gravitating to Clients Who Require Customization | |
| – Mobile Integration | |
| – Fraud and Security Crossover | |
| – Provider Network's PBX is More Protected | |
| – Analyzing SIP-based Registrations | |
| – A Layered Strategy Works | |
| B. Telinta Hosted Softswitch: Affordable Entry for Comms Entrepreneurs | |
| – Hosting Telecom Businesses in the Cloud | |
| – VoIP Providers Selling the Full Range of Services | |
| – Hosted PBX Services for VoIP Providers | |
| – Telinta's Telicore Hosted Telecom Cloud Platform | |
| – Virtual Office Services for Telecom Entrepreneurs | |
| – Mobile Extensions to the Hosted PBX | |
| – A Telco Business for a Few Hundred Dolllars a Month | |
| – Entrepreneur Firm is Trained to Configure its Services | |
| – Partners Needed for Everything Outside Switching & Billing | |
| C. Blocking IRSF Fraud at the SIP Session Border Controller | |
| – Overview of the US VoIP Provider Market | |
| – TransNexus and its Ooma Customer | |
| – A $166,000 IRSF Charge to a Small Architecture Firm | |
| – How TransNexus Got in the Business | |
| – The Problem with CDR Analysis in Fraud Detection | |
| – The Virtues of Fraud Blocking via SIP-Signaling | |
| – TransNexus Manages its own IRSF Blacklist | |
| Chapter 12. Business & Revenue Assurance (46 pages) | |
| A. Subex Juggles a Variety of Business Assurance and Big Data Analytics Use Cases | |
| – The Variety of Business Assurance Cases | |
| – Subex Opportunities on the Horizon | |
| – The Shift from RA to Business Assurance | |
| – 1. Security for IoT | |
| – 2. Optimizing the Use of Network Assets | |
| – 3. Big Data Analytics & AI Use Cases | |
| – 4. Massive Multiplayer Online Gaming Assurance | |
| – 5. Assuring the Rapid Onboarding of Mobile Subscribers | |
| – 6. AI-Powered Customer Credits & Complaint Analysis | |
| – A Framework for Machine Learning | |
| B. TELUS Analytics Team Telemetry Delivers Internal Business Assurance Campaigns | |
| – Internal Team of Data Analytics Experts for Hire | |
| – Mission of the Telus Telemetry Team | |
| – What Telemetry Does to Benefit Internal Users | |
| – Why Telus Chose the WeDo RAID Platform | |
| – Engaging with Various Departments at Telus | |
| – Driving Predictive Analytics Campaigns for Users | |
| – The Evangelical Role of Telemetry's CMO | |
| – Telemetry's Growth Plans | |
| C. Dynamic Reference Data: Symmetry Helps O2 UK with Data Governance & Master Data Management | |
| – The Challenge of Synchronizing Legacy Platforms | |
| – Symmetry's Proven MDM Platform at O2 UK | |
| – The Scope of Reference Data Work at O2 UK | |
| – Reference Data and Enterprise Contracts | |
| – The Variety of Reference Data Use Cases | |
| – How a Reference Data Systems is Built for a Telco | |
| – Reference Data Uses in RA, Fraud & Risk | |
| – The Value of Reference Data | |
| – Turning Complex Processes into Managed Services | |
| – Cloud Based MDM Attractive to Group Operators | |
| – A Recipe for Managing Business Speed | |
| D. From Byzantine Software Contracts to Simple & Flexible RA Managed Services | |
| – Why Traditional B2B Software Delivery is Byzantine | |
| – The Value of a Mnaaged Service in RA/Billing Verification | |
| – A Managed Service vs. Internal Purchased Software | |
| – Is Operating Test Call Robots a Core Mission of RA? | |
| – Managing Full Billing Verification Campaigns | |
| – Contract Flexibility in Revenue Assurance | |
| – Six Factors to Look for in an RA Managed Service Provider | |
| E. Telecoms Failing CAPEX: The Need for Asset Management & Financial Visibility | |
| – CAPEX Spending Often Out of Control | |
| – Why Network Assets Must be Tracked Through Full Life Cycle | |
| – How Subex Solution Manages Network Assetrs | |
| F. Network Asset Choreography: Subex's Discovery & Life Cycle Management | |
| – Massive Intelligence Required to Manage Network Assets | |
| – Issues around Decommissioning Network Assets | |
| – Choreographing Network Equipment | |
| – Coordinating Network Assets & Warehouse Inventory | |
| – The Role of ROC Data Integrity Management | |
| – Insights & Predictions for Network Capital Strategies | |
| – Analytics Drives Optimal Asset Use & Capital Avoidance | |
| Chapter 13. Machine Learning & Exponential Technologies (35 pages) | |
| A. Mobileum Attracts Operators to its IRSF-Analyzing & Opex-Saving Machine | |
| B. Deep Fraud Investigations: Mavenir and the Role of Machine Learning in IRSF Control | |
| – Mavenir, the un-NEP Telecom Software Provider | |
| – Native Integration of Fraud and Security | |
| – Why Native Network Integration Has Value | |
| – The Difference between Rules and Machine Learning | |
| – Analyzing Roaming Records for NRTRDE Advantage | |
| – Finding Active Roaming Customers who are Fake | |
| – Why Behavioral Analysis has Power in Fraud | |
| – Network Element Monitoring for Security | |
| – Verifying Identity in 5G and IoT | |
| C. MTN Agility: Mastering Exponential Technologies in Revenue/Fraud Assurance and Beyond | |
| – Waht Computers Won't Do | |
| – Backgrounds of MTN Experts | |
| – MTN Group's Broad Business in Africa and ME | |
| – Key Challenges in Fraud and RA | |
| – Maturity Gains and Success in Assurance Ops | |
| – MTN on Monetizing the Benefits of RAFM | |
| – Organizing the Innovation Team | |
| – Bringing In Exponential Technologies | |
| – Redesigning Ways of Doing Risk/Assurance | |
| – Making All OPCOs Agile with Co-Design | |
| – Fast Prototyping Examples at MTN | |
| – The People Motivating Side of Innovation | |
| – Assessment of RAFM Solution Vendors | |
| – A Shift Targeted Platforms & Business Assurance | |
| – Will Big Digital Vendors Enter the Telecom Solution Biz? | |
| – The Strategy Moving Forward at MTN | |
| D. False Answer Supervision Solution by IPsoft | |
| – The History of Arbinet and IPSoft's Business | |
| – What is False Answer Supervision (FAS)? | |
| – Statistical Analysis is Required to Detect FAS | |
| – Tight Margins on Voice Traffic Raise the Importance of FAS | |
| – The IPSoft FAS Detection Process | |
| – Statistical Analysis Requires Data Scientists | |
| Chapter 14. Assurance & Fraud Control Best Practices (43 pages) | |
| A. How to Instill a Strong Telecom Risk & Anti-Fraud Culture | |
| – The Vital Role of Industry Consultants | |
| – The Challenges of the African Market | |
| – Financial Infrastructure on the African Continent | |
| – Educating Consumers on Mobile Device Security | |
| – Educating Telcos about Fraud/Risk Education | |
| – The Revenue Assurance and Marketing Partnership | |
| – Risk Reward Awards Recognizes Achievers | |
| – Perspectives on the Value of Industry Forums | |
| B. Nine Simple Strategies to Protect an Operator or MVNO from Telecom Fraud | |
| – Jim Bolzenius, Former Verizon Fraud Director | |
| – International and Domestic Fraud Methods | |
| – Subscription Fraud & Identity Issues | |
| – 1. Make Timely Detection & Blocking your Key Goal | |
| – 2. Use Social Network Analysis to Multiply Your Blocking Capability | |
| – 3. Don’t Make PBX Hacking Easy for the Fraudster | |
| – 4. Educate Customers & Call Center Reps about Social Engineering Schemes | |
| – 5. Implement Processes to Limit the Wangiri Fraud | |
| – 6. Control or Turn Off Dangerous Calling Features & Destinations | |
| – 7. Monitor and Test your International Roaming Rules | |
| – 8. Don’t Let Your Guard Down over the Holidays | |
| – 9. Recognize that a Fraud Management System Alone is Not Enough | |
| C. Telecoms Need to Improve Subscription Fraud and Customer Onboarding Control | |
| – Acquiring Customers at Low Cost & Minimum Risk | |
| – A Robust Onboarding Process for Mobile Subs | |
| – Mobile Phone Activity: a Great Risk Mitigating Tool | |
| – Demand for Money Laundering Controls | |
| – Managing Risks in Smaller Slices | |
| – Steps in a Successful Customer Engagement | |
| – Fraud vs. Revenue Assurance Data Management | |
| – Solving Integration Complexity Issues | |
| – The Vital Need to "Know Thy Customer" | |
| D. Applying Steve Jobs' Leadership Tenets to Telecoms and Business Assurance | |
| – Ed Shanahan RA Consultant | |
| – Simplicity, Organization Focus & Patience | |
| – Telecom as a Horizontal Business Flow | |
| – Maintaining Business Simplicity | |
| – Careful Hiring and Attention to Compensation | |
| – Alignment of Compensation with Company Goals | |
| – Compensation of Sales People | |
| – Getting Sponsors for Business Assurance Goals | |
| – How Would a Steve Jobs Run a Telecom? | |
| E. Make Business Assurance Progress Every Day: Set Goals, Automate, and Energize Your Team | |
| – Executives: a Driving Force in Assurance Excellence | |
| – Managing Payment Processes | |
| – Enabling Customers to Pay Any Way they Like | |
| – Keeping the Customer Informed | |
| – Reconcilation of Payments is Similar to RA | |
| – Energizing Staff to Grow and Make Things Better | |
| – A Healthy Skepticism over Full Automation | |
| – Putting Yourself in the Shoes of the Customer | |
| F. A Herculean Task: Battling Fraud in a Complex Comms World | |
| – Michalis Mavis, Former Head of Fraud Control at OTE, Greece | |
| – Fraud Losses Big During Year of Olympic Games | |
| – Brief History of Large Fraud Losses | |
| – Case of the Criminal Ring on the Island of Crete | |
| – Interconnect Fraud | |
| – Perspective on FMS Tools | |
| – Fraud Challenges Going Forward | |
| – Four Key Initiatives in Fraud Control | |
| Chapter 15. Mobile Monetization (38 pages) | |
| A. SIGOS's Purpose-Built Analytics Platform: Mobile Money, SIM Box Fraud, and More | |
| – Digital Business Market Change & Competition | |
| – The SIGOS Purpose-Built Approach to Telecom Analytics | |
| – Example of CDR Handling in Nigeria | |
| – Big Data without Querying a Database | |
| – The Privacy Problem with Cloud Solutions | |
| – Dedicated Use Cases Supported by SIGOS | |
| – Three Differentiators in SIM Box Bypass Solutions | |
| – Success in Ridding a Country of SIM Box Bypass | |
| – The Mobile Money Opportunity in Developing World | |
| – A Soup-to-Nuts Mobile Money Solution | |
| – The Goal of Being the Performance Leader | |
| B. Mavenir & Syniverse Platform for RCS Business Messaging | |
| – The Race to Deliver RCS Business Messaging | |
| – The Future is P2A Messaging | |
| – Mavenir's Messaging-as-a-Platform | |
| – Syniverse's Role in Securing the RCS Business | |
| – The Mavenir and Syniverse Partnership | |
| – Capex or Revenue Share Model for Operators | |
| – RBM Solves the Dumb Pipe Problem | |
| C. HGC Taking its Digital/Carrier Expertise to Asia's Emerging Markets | |
| – The Financial Success of Digital Companies | |
| – About the HGC Business | |
| – HGC's Value Proposition as a Telecom Firm | |
| – A Local & International Firm | |
| – The Economic & Digital Maturity of Asian Nations | |
| – Asia Adapts to Digital LIfe Very Quickly | |
| – Opportunities in Telecom Service Mix | |
| – The Role of Chief Digital Officer | |
| – Managing the Tough Projects is an Opportunity | |
| D. A Big Win/Win: Protecting Mobile Users While Boosting Revenue | |
| – Real-Time Cloud Services in Mobile | |
| – Allot's In-Line Malware Blocking and Web Protection for Consumers & SMBs | |
| – Details & Benefits of a Proven Cloud Security Service | |
| – The Business Challenge of Mobile | |
| E. Mavenir Merchandizes Data Rewards: A Clever Program that Creates Value for Brands, Users, and MNOs | |
| – Delivering Merchandizing Shrewdness in the Mobile World | |
| – A Brief History and Project Growth in Mobile Advertising | |
| – Creating a Win for Users, Brands, and Carriers | |
| – Rewards Programs Were Pioneered in the Gaming Industry | |
| – How a Data Rewards Campaign is Run | |
| – Engaging with Brands via Zero-Rating vs. Data Rewards | |
| – Coca Cola’s Branding Campaign using Data Rewards | |
| – A Campaign for Mondelez’s Candy Brand “5star” in Brazil | |
| – Exxon Mobil in Mexico – A Direct Response Survey | |
| Chapter 16. Free-Wheeling Discussions with Consultants Colin Yates & Luke Taylor (18 pages) | |
| A. Strategic Discussion with Consultant Colin Yates | |
| – Rules Based vs. Machine Learning IRSF Protection | |
| – IPRN Provider and IRSF Trends | |
| – IPRN Numbers & Arbitrage via “Unlimited” Calling Plans | |
| – How IPRN Provider Arbitrage Works with a Human Caller in Morocco | |
| – How to Control Arbitrage via “Unlimited” & Roam Like Home Packages | |
| – The Special Case of Protecting MVNOs | |
| – The Role of Fraud Analyst as the Machine Learning Age Dawns | |
| – Managing Fraud at Group Operators | |
| B. Strategic Discussion with Consultant Luke Taylor | |
| – AI/Machine Learning vs. Human Analysis | |
| – The Move Away from Big Bang Assurance and Analytics Solutions | |
| – Generic Assurance Platforms vs. Solving the Customer’s Key Issue | |
| – The Purpose-Built Platform and Working Across Silos | |
| – Why Telecom Needs Chief Data Officers | |
| – The Rising Importance of Data Governance & MDM | |
| – What Operating Agility Means in Today’s Competitive Telco World | |
| – The Power of a Modular Assurance & Analytics Platform | |
| – The Premium on Multi-Talented Business People and Experienced Teams | |
| Chapter 17. Market Analysis & Forecasts (22 pages) | |
| A. Research Objectives & Methodology | |
| – Research Scope, Contents & Expert Contributors | |
| – Research Methodology | |
| – Method of Forecasting and Estimating Market Size | |
| B. Big Picture Analysis and Overall Forecast | |
| – State of the BA/FM Profession & Solutions Market | |
| C. The Fraud Control Profession and Market | |
| – Telecom Fraud Management Solutions Market by Fraud Type | |
| – A Frequent Executive Blind Spot: Fraud is a Wind that Always Blows | |
| – The Fraud Solutions Market: Vendor Market Share | |
| D. Revenue Share Fraud | |
| – Defining Revenue Share Fraud | |
| – The Four Primary Solution Types Tackling the Fraud Today | |
| – CDR- and Usage Profile-based Solutions | |
| – Hybrid Revenue Share Solutions: CDRs and SIP | |
| – Machine Learning Solutions | |
| – Enterprise PBX Protection Resale | |
| – The Roaming/Global Network Connection | |
| E. Other Fraud Types | |
| – SIM Box Bypass Fraud | |
| – “Roam Like at Home” Services Open Up Voice & SMS Fraud | |
| – Battling Data Theft and the Insider Threat | |
| – The Importance of Law Enforcement to the Fraud Fight | |
| – Analyzing Digital Behaviors Key to Identity & Subscription | |
| – Reassessment for VIBER Mobile Bypass | |
| F. Business, Revenue, & Partner Assurance | |
| – The Rising Opportunities in Business Assurance & Analytics | |
| – The Business Assurance Market: Vendor Market Share | |
| G. Business Assurance Developments and Solutions | |
| – The Modular All-Purpose Platform | |
| – Customized Business Assurance Solutions | |
| – Large Carrier Efforts to Exponential Tech Inside | |
| – IoT Management of Device Identity and Use Case Profiles | |
| – High Performance Network-Resident System & Managed Services | |
| – Dynamic Reference Data Management | |
| H. Mobile Monetization and Mobile-to-Brand | |
| Chapter 18. Vendor Profiles (28 pages) | |
| – Arraxe | |
| – LATRO Services | |
| – Oculeus | |
NOTE: More vendor profiles will be emailed to Report buyers as vendors purchase the Report and TRI completes their profiles. | |