The pandemic has forced individuals to opt for digital transactions over face-to-face interactions. Unfortunately, the proliferation in digital transactions has led to an alarming rise in online identity fraud, often executed by fraudulently taking over a consumer’s phone.
A report by Atomik Research found out that 74% of financial institutions in the UK and the US experienced a surge in cyberthreats linked to COVID-19. About 37% of them believe their customers are now at greater risk of cybercrime or fraud. Identity theft, account takeover, and online fraud are forcing financial institutions to implement more stringent identity verification and authentication practices. However, strengthening fraud prevention leads to a high number of false positives, resulting in poor onboarding experience and customer service.
Fraudulent SIM swaps and the difficulty in quickly identifying them are the key reasons for false positives. SIM swaps are on the rise, especially in the UK. The highest number of SIM swap cases were recorded in 2018, where the cumulative loss was £2.9 million from 3,111 fraud cases. In the first half of 2020, 483 SIM swap cases were recorded in the UK, resulting in a loss of £839K; the average loss for a user amounted to £2,567. In 2015, there were just 144 cases of SIM swap fraud.
Currently, banks are collaborating with telcos to tackle SIM swap; they validate SIM swaps and porting data within a stipulated cut-off time. Original phone owners get enough time to contact their network provider when they discover that their SIM has been swapped without their knowledge. The downside is that customers who have legitimately ported their SIM cards fall into a false positive queue and are subjected to unnecessary delays in verifying their identity.
Financial institutions can address SIM swap fraud by adopting a risk model that analyzes various device- and phone number-related attributes from authoritative sources at the time of a transaction and indicates the level of trustworthiness. Such a model leverages advanced algorithms on phone data and intelligence aggregated from multiple sources to assign a reputation score for an individual’s phone number—the higher the score, the higher the pass rate. A high score will also greenlight more genuine customers, thus eliminating false positives.
Prove’s Trust Score™ is a real-time measure of a phone number’s reputation that uses behavioral and phone intelligence signals to measure fraud risk and identity confidence. Trust Score performs many real-time checks, including a SIM swap check, to calculate a real-time Trust Score. A low Trust Score is an indicator to apply the appropriate authentication policy, such as rejecting the transaction, not sending the 2FA code by SMS, or redirecting them to manual scrutiny by an agent.
Trust Scores run on a scale from 0 to 1,000, with a higher number indicating a higher Trust Score. Trust Scores over 630 are typically considered ‘high,’ and scores 300 and below are categorized as ‘low.’ Trust Score’s risk model examines phone intelligence signals such as phone tenure (SIM tenure, tenure of device), line attributes (active number, number porting, mobile status, available network status, and line type), account activity (change event occurrence velocity), and device activity (device ownership tenure) to calculate the level of risk.
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