Problem overview
Detecting social engineering scams poses a significant challenge due to the fraudster's avoidance of direct interaction with the banking platform. Instead, they manipulate the victim into initiating the payment personally. Consequently, traditional fraud detection methods become ineffective as legitimate users log in to their accounts from their own devices and locations, and also provide appropriate authentication credentials to carry out the payment.
By leveraging behavioral insights, financial institutions can claim back the advantage over fraudsters. The key lies in analyzing the account holder's behavior during their banking session. Paying attention to indicators, such as suspicious mouse and phone movements, hesitation, and the dictation of account numbers makes all the difference when trying to win the war against scams and fraud.
Continuous Behavioral SequencingTM
The only way to stop social engineering voice scams before the damage is done.
On desktop:
signs of doodling
20% of mouse doodling is normal. 40%–60% of mouse doodling is indicative of a hesitant victim.
On mobile:
signs of guidance
Phone movement can suggest a user is moving the phone to and from their ear, indicating a fraudster could be dictating a destination account number to the victim.
Authorized Payment Fraud:
A Global Guide
Online banking has been quickly evolving into an immediate-payment world, and consumers have come to expect the ability to instantly send and receive funds.
However, faster financing has led to faster fraud for criminals. And it’s now more convenient than ever for fraudsters to exploit victims quickly and easily.
Read our white paper that explores the current regulatory landscape related to unauthorized and authorized payment fraud in eight different countries.
use cases
Impersonation scams
Remote access attacks
Peer-to-Peer fraud
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