when big data analytics meets fraud prevention eisner_final.pdfbig data analytics in fraud...
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© 2014 – PROPRIETARY AND CONFIDENTIAL INFORMATION OF CVIDYA
When Big Data Analytics
meets Fraud Prevention
Daniel Glebocki - Director of Fraud Management-Orange Israel/012 smile
Tal Eisner - Senior Director Product Strategy-cVidya
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A leading supplier of Revenue Analytics solutions to communications and digital service providers
Founded: 2001
300 employees in 15 locations worldwide
Deployed at 7 out of the 10 largest operators in the world
150 customers in 64 countries
Processing 2.45 Billion subscribers in deployments globally
Saving over $12 Billion to providers annual revenue
Partnering with world leading vendors
What You Should Know - cVidya
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Turning your DATA into VALUE
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An Entire New Ball Game
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VISION: To create a world where everything intelligently connects via mobile networks, delivering rich services to businesses and consumers in every aspect of their lives (GSMA, Connected Living, November 2013)
Connected Living
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Some Numbers
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New Fraud Management ChallengesNew Fraud Management Challenges
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� Fraud units need to process & control extraordinary volumes of data which
entails:
– Info sources that did not exist before
– Extensive use of external sources e.g., social networks
– Cross analysis of non-associated sources of info
– A new set of risks and threats to be identified & controlled
– A whole new terminology to master and areas to cover
Finding Poisoned Fruit Trees In The Forest
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Someone Is Moving My Cheese…
� Usage-based Voice Fraud becomes less relevant
� Real-Time Self Provisioning :
– Encourages Acquisition / Subscription Fraud
Issues
– Encourages Account Takeover
� Price Plan Abuse / Out-of-Bundle Usage
� “Controls” at POS are less relevant
– Virtual POS systems become the norm
– A shift towards OTA control
� Need for external sources for essential investigation
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� Manual, long-term investigation process changes to quick, fast and detailed retrieval of info
� Processing xls. sheets, human intelligence and long hours of manual analysis – have changed into an effective alerting mechanism of valuable insights
� BD Platform enables storing and analysis of info sources that were not available in the past, and in significantly larger retention
� Enabling the Fraud Unit to provide services and leverage capabilities for other non-fraud activities
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Big Data Analytics in Fraud Management
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� Significantly helps in areas such as:
─ Analysis of unfair use and out-of-bundle data
─ Security matters for which info is needed “here and now”
─ Info sharing and intelligence gathering via Web data
─ Internal fraud investigations
Quicker, Richer, Better
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Analytics for Internal Fraud Analysis
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Internal Fraud
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� Controlling sales personnel requires extensive use of:
─ Feeds from social networks─ Retention of wide-ranging historical data─ Traffic control of customers
─ Analysis of sales contracts─ Detailed control over internal systems─ CRM logs and information
Tedious “ant work”. . .
Big-Data oriented
Information
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Internal Fraud Disclosure by Analytics
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� Obtain relevant processes and controls are put in place to
monitor internal sales procedures:
─ Average sales per rep per day─ Who are the customers? What services are being sold?─ What social feeds are being posted?─ Transactions in billing and CRM applications─ Characteristics of car usage by sales rep─ Communication forensics of sales rep
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...And More
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� Controls are in place for monitoring new customers activated
by sales rep:
─ Trends and patterns of usage ─ % of credit and collection issues─ % of fraud cases in history─ Connections between known fraudsters─ Calls from customers to known high-risk destinations
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Cross Source Analysis For Fraud Insights
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Social Networks
CustomerManagement
Finance,Accounting,
AR,Collection
Rating &Billing
Network & Usage
Management
ContractsAudit
CarUsage
Analysis
Fraud Alert
Apps LocationSocialFraud
History
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Results
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� Activation average - Up 267%� VAS activation - Up 153%� Benefits given to new subscribers - Up 218%� Intercepted anti-company posts on rep’s Facebook Wall� Car KM/Fuel consumption - Up 233%� Major adjustments in CRM system made during non-business
hours� Over 70% of subscribers had credit / payment issues during
1st billing cycle
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Results (Cont.)
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� Combination of the above provided strong indications for fraud by reps
� Info received in near real time� Only by cross analyzing are such insights made possible � With traditional investigation methods, similar
accumulation of info could have taken weeks!
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Analytics within the Big Data enables
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� Real-time retrieval of actionable alerts from cross sources:
─ Saves days of manual work ─ Strengthens independence and minimizes dependency on
other departments for info─ Alerts on deviations from patterns of sale─ Provides strong indications of fraudulent activities─ Gives insights into new trends of fraud by employees─ Provides valuable information on business level and
quality of work
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Significant Indicators For Fraud
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Trends and Patterns - Quicker ,Richer, BetterAlerts
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More Ahead . . .
In the near future, Fraud Investigators will have to connect to
even more external sources of info to “complete the big
picture”:
─ OTT Application Content─ Unstructured Data─ Mobile Payment Platforms─ M2M
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� Data tsunami and fraud risks inflation highlight the need for an automated mechanism
� Analytics provide what fraud management has always needed:
– Patterns & Trends
– Cross analysis of non-correlated sources of info that were not used in the past
– Alerting of deviations
– Significant reduction of false positive
– Accurate, fast & intelligent insights
� Dramatic reduction of time & investigation resources
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