Financial sign-up bonuses are hot these days. Whether you are opening a new bank account or signing up for an online checking account, financial institutions are paying out hefty rebates to get your business.
What is a financial sign-up bonus?
A sign-up bonus is essentially like free money in your pocket. That’s right – legitimate companies will pay you to use their services by rewarding you with excellent sign-up benefits. Typically, there will be some requirements you’ll need to meet, such as being new to the service or spending a certain amount within a few months of account opening.
For banks, sign-up bonuses are an excellent marketing tool. While companies increase the number of customers that sign up for their services, you get to enjoy free cash-back or other perks for making use of the service. This makes financial sign-up bonuses a win-win situation for both customers and financial institutions alike.
Not all lovey-dovey.
Sign-up fraud is not dominated by savvy fraudsters. Unlike other types of fraud which require a complex operation, creating fake accounts is somewhat simple and fraudsters leverage such promotions that bite into the banks’ profit.
Sign-up bonus abuse can range from innocuous – like a hacker creating multiple fake accounts to get a 10% rebate – to sophisticated, organized costly hacks. Referral programs, where customers receive benefits for referring friends to a financial institution are particularly lucrative targets for fraudsters.
How can financial institutions prevent sign-up bonus abuse?
Financial institutions can bolster their ability to detect and block fake accounts that take advantage of such programs. Many attempts at sign-up bonus abuse can be prevented by stopping single users from opening multiple accounts. How? A multi-layered analysis often identifies abnormal behavior. A thorough review of users opening multiple accounts using the same device – is a good start. Another way to prevent sign-up bonus fraud is to monitor user behavior post account creation (behavioral biomerics). Once an account starts exhibiting suspicious behavior, like abnormal account usage or an idle account, the financial institution is very likely to be defrauded.
This is exactly where Paygilant comes-in. Paygilant helps financial institutions distinguish between good customers and fraudsters. Its solution is designed to detect such fraud, using six separate fraud intelligence sets that determine, whether the activity is legitimate or fraudulent. Paygilant operates at several data layers including user behavior, user device, user transaction, and human/non-human activity. This is used to weave an identity representation of the user, providing a score that indicates the risk level prior to processing the transaction/payment.
