Fraud Analytics in Telecom: SAVIOR of Bad Times
Fraud vs Analytics: War of Numbers
Global Telecommunications industry estimate the fraud to be one of the most acute and persistent problems. Estimates of yearly fraudulent losses run up to $10 million according to industry reports.
Telecom Fraud is any dishonest or illegal use of services, with the intention to avoid service charges. Fraud detection is the name of the activities to identify unauthorized usage and prevent losses for the mobile network operators. There are n-number of such instances when the Telecom Companies realized the acceptance of Analytics as part-n-parcel of their Business Core though they may or may not actually implemented it. But when it comes to Fraud instances, it becomes inevitable for most of them to go for a scalable yet efficient solution to detect and eliminate fraud.
There exists two types of Fraud in Telecom:Subscription & Superimposition fraud.In addition,we also have Technical and Internal Fraud ,though both of them can be tapped and eliminated via Inbuilt Ecosystem of the company.But when it comes to Prior two’s,need of a robust analytical solution becomes a necessity.
Subscription fraud occurs when a customer opens an account with the intention of never paying for the account charges. Superimposition fraud involves a legitimate account with some legitimate activity, but also includes some “superimposed” illegitimate activity by a person other than the account holder.Superimposition fraud poses a bigger problem for the telecom industry nowadays.
Analytical persons and engineers over the years came up with numerous solutions to tackle the devil like:
- 6Sys structure:Detection-prevention-analysis-prediction-alarm-control
- 4Model:operation-customer-TFAC system-Warehouse datamart – data mining analysis
- 4Analysis:predefinition analysis-Ad Hoc Analysis-OLAP Analysis-Data mining analysis,etc
In simple terms, Fraud detection is done mainly by identification of the misusing customer and malpractice customer in the telecommunication area for which analyst use Pattern finder via algorithms like: Apriori, GSP,SPADE, Prefix Span and Spam.
At the back-end there are few heroic statistical techniques which are doing the magic such as Genetic algorithms ,which is one of the best way to solve a problem for which little is known.
Genetic algorithms use the principles of selection and evolution to produce several solutions to a given problem.