Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
The Great Unknown - How can operators leverage big data to prevent future revenue losses in the data based world
1. These are the voyages of cVidya in its quest to battle big data fraud
and to boldly go where no fraud solution has gone before
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Key Facts
Canada
Brazil
Guatemala
South Africa
Israel
Spain
UK Ukraine
India
Singapore
Bulgaria
USA Macedonia
cVidya is a leading supplier of Analytics solutions to communications and
digital service providers. cVidya’s big data technology platform and
analytical applications enable operators to optimize profits and enhance
decision-making.
160+ customers in 64 countries
300 Employees
Founded 2001
Leading Provider of Analytics Solutions
Business success with proactive revenue assurance (2013)
TM Forum Leadership (2012)
Partner Network Specialized Award (2012)
Revenue Analytics & Fraud Mgmt leader (2012)
Revenue Management leader (2012)
Most innovative vendor (2012)
#1 Revenue Management Global Market (2011)
Serving 7 out of the 10 largest operators in the world
Global Footprint – 13 locations worldwide
Industry RecognitionCustomer Base & Partnerships
Partnership with leading global vendors
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Interpreting Big Data Hype
When new technologies make bold promises, how do you separate the hype
from what's commercially viable? And when will such claims pay off, if at all?
5. 55
Big Data Analytics
"Data is widely available,
what is scarce is the ability
to extract wisdom"
Hal Varian, Chief Economist, Google
6. 66
What Do We Provide?…
cVidya provides an analytical platform embedded with
best practices use cases for different purposes such as RA,
FM, Marketing Analytics & Data Monetization - all using
industry standard big data environments
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New Fraud Challenges
The telecom market is in a dramatic transition
phase that influences the fraud department’s
challenges and activities
What new types of risks are out there?
What needs to be monitored?
Using what tools?
How do we support the enormous amount of data
and find the “needle in the haystack?”
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According to the latest CFCA report
(published in 2013) there is a 15%
increase in fraud losses (compared
to 2011)
PBX hacking, PRS/IRSF, bypass and
subscription fraud still cause the
industry damages of billions of $
annually
Traditional Fraud is Still a Major Pain
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Operators need to balance between getting to
know the new and emerging types of fraud,
and coping with the traditional types
that still cause them major damages
9
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Fraud detection and prevention through DPI
− DPI reveals new areas that up till now weren’t covered - allowing for detection of
new types of fraud types and service abuse
− The amount of DPI transactions is tremendous!
− BD capabilities are a must when dealing with DPI information
Some examples of fraud scenarios which can only be detected using DPI:
− Abnormal usage Analysis
− Proxy Fraud - Disguising premium data traffic to avoid additional payments
− IP PBX hacking detection - Toll fraud conducted by fraudsters by compromising
corporate IP PBX
− Tethering - Revenue loss to the operator due to sharing of a single Internet
connection by several devices
Case:
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Abnormal Patterns Analysis
The Issue
− Fraudsters commit mobile / e-commerce fraud while accessing
websites from their smartphones / tablets
− Mobile / e-commerce companies can only detect fraud
attempts on their own websites
The Solution
− A DPI-based solution that enables telcos to monitor and detect
the OTT activity of the mobile data user
− The solution looks for suspicious behavior in the entire
network
Business Value
− Telcos can offer / share the insights gained from monitoring
activity
− Providing mobile / e-commerce companies with insight into
fraud committed across the network
− Enables mobile / e-commerce companies to reduce their
exposure to fraud
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Abnormal Patterns Analysis – Use Case
The system characterizes what is defined as “reasonable” usage
patterns of a normal user in the network and alerts abnormal
behavior
Normal user browses several websites throughout the day,
attackers will most probably access only the targeted website)
Number of accesses to specific websites should be reasonable
(Multiple accesses to eBay or Amazon are suspicious)
Sequential destination port numbers
A “normal” mobile data user / subscriber profile is based on the DPI
component that reveals the applications and services being used by
the user
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Proxy Fraud
Issue Disguising premium data traffic to avoid
additional payments to telcos
Need
Telcos are moving to advanced billing schemes
Detects users that are trying to bypass the billing
processes / avoid additional charges
solution A DPI-based solution that enables telcos to
detect such disguised traffic
Business
Value
Telcos can recover lost revenues
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Proxy Fraud (Cont.)
Users connect to proxy services (located outside / beyond the
ISP network) that allow them to connect to the requested
website preventing the ISP from monitoring and billing this
activity.
By using DPI the fraud system can use SSL protocol to detect
disguise proxy activity.
The DPI record demonstrates using YouTube using an
encrypted protocol and destination IP which doesn’t belong
to YouTube subnet
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IP PBX Hacking Detection
The Issue
− Toll fraud is being performed by compromising corporate IP PBX
− Recent CFCA-reports estimate fraud damage at > $4.96B per annum
The Need
− Organizations are legally liable for fraudulent traffic in their networks and
must proactively monitor their PBX activities and detect hacking attempts
The Solution
− An IP probe / DPI device located within the corporate LAN
− The device monitors abnormal PBX port scanning activity
Business Value
− Detects the hacking attempts effectively
− Performs corrective actions to remove all malicious devices within the
network
− Prevents PBX hacks / toll fraud
20. Massive parallel processing
P = Performance
Scalability & linear growth
Longer retention time
Shorter processing durations
Wider back office processing & analysis
C = Cost
Reduction in HW & SW licenses
Commodity hardware
& storage
Better planning &
targeting
High availability
Historical & Real-time data
C = Coverage
Verticals & LOBs
Multiple sources & systems
Multiple departments
Structured & Unstructured
Centralized platform
Multiple user types
20
Big Data
Analytics
Benefits
- cVidya Big Data Analytics Platform BenefitsC2P
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A new initiative of the TMF - Unified Analytics
Big Data Repository (ABDR)
Supports multiple use-case & analytics systems
Data repository of loosely coupled data entities
Standard definition using data dictionary
Benefits
Avoiding data replications
Saving in ETL costs & time
Faster time to implement new use-cases
Open platform
ABDR
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Real-time
Event Queuing
Big Data Architecture
Unified
Analytical
Layer
Data
Node
Data
Node
Ad-Hoc
Reports
Real-time Streaming Component
Data
Node
Map Reduce
Data
Node
Business
Widgets
Case
Management
…
cVidya’s Unified Analytics
Business&
OperationalDashboards
Premodeled
CustomerData
Applications
Columnar Data Base (Optional)
MoneyMap® Plus| FraudView® Plus | Enrich™ | Engage™
cVidya’s Big Data Platform
Real-time
Comparison
Advanced
AnalyticalModels
All Data Sources
CRM
Mediation
ERP
IP&DPI Probes Switch
Billing DWH
Order & Provisioning
cVidya’s ETL
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Why cVidya
cVidya is leading the way with Big Data
Expanded RA, Fraud and Analytics products to
support big data based infrastructures
− Leveraged the latest Big Data technologies to
enable enormous data volume processing and
advanced analytics
− Leading the TMF ABDR project - Analytics Big
Data Repository