Fraudsters are always looking for their next easy target to exploit your vulnerabilities for their profit. Staying ahead of these scams is always a challenge, especially in the telecommunications industry. Everyday new types of schemes are wreaking havoc on wireless carriers and negatively impacting their bottom line.
While there are several types of point of sale fraud, there is one scam that continues to grow. It’s a form of identity manipulation. Instead of stealing another person’s identity or personal information and using it once, fraudsters use their own identity, a lent one (mulling), or a stolen one, as many times as they can. They leverage latencies between systems to maximize the abuse. During this time, they buy several phones and/or tablets in the same day from multiple carriers or over a short period of time, before an initial bill is received or abuse is detected. All that these fraudsters do is subtly switch a digit in their address, a letter in their last name, day or year of birth, or social security number, in the hopes that during the identity verification process, inconsistencies in their data won’t be detected and associated with a previous transaction. Often this works, allowing fraudsters to leave the store with a $700+ smartphone, with little to no money down and no intention to pay. Their only plan is to resell the smart phone for a hefty profit.
According to the Communications Fraud Control Association (CFCA) 2015 Global Telecom Survey, carriers lose more than $38.1 billion each year due to fraud, making it critical to put the right fraud detection solution in place.
Fortunately, big data analytics has given carriers a tool to combat the issue.
Although identity manipulation is different than other types of fraudulent activity, it’s still considered an unauthorized tampering or manipulation of data.
The fact remains that identity manipulation fraud is growing fast and stopping it begins by rethinking fraud detection at the point of sale and how carriers can help save their own revenue.
That’s where velocity checks come in.
But, what exactly is a velocity check?
A velocity check, or a frequency check, is a critical first step in fraud prevention. This helps identify transactions that “seem” to originate from different individuals, but really come from the same person. These transactions will have similar identifiers (e.g. email address, phone number, credit card number, billing address and shipping address) and originate within a short period of time. Velocity checks provide ways to identify, and therefore reject, any suspicious transaction. It also alerts the carrier and allows the provider to manually review the information before they engage in a risky transaction.
If a carrier detects fraud after seeing that a customer has signed up for say, several phone plans during the past 24 hours, they can elevate the issue to ensure that the customer is dealt with legally, preventing them from losing another $700 phone.
To implement velocity checks, a wireless carrier needs to deploy a real-time point of sale fraud management solution. The system needs to process new service applications in real-time and return a “go” or “no-go” decision inflight at the point of sale within less than four seconds – which is as quick as walking 7 steps.
Quality velocity checks use a sophisticated analytics engine that includes identity analytics, cluster analysis and a matching and scoring algorithm to identify patterns, sense irregularities in data and then uses those irregularities to define correlations.
The solution must also smoothly integrate into the order processing systems used by the carrier’s call centers, retail outlets, websites and reseller’s store fronts.
Cellphone carriers are set to lose millions this year due to point of sale fraud. But implementing a fraud management solution with velocity checks offers end-to-end authentication to help identify potential identity fraud, saving the carrier money and minimizing losses.
To learn more about using data analytics to prevent fraud, download this case study.