Identity Theft, Catch Me If You Can

Written by RibbitWebAdmin

September 15, 2021

The biggest problem in the world could have been solved when it was small ~ Bynner

Identity theft is running rampant; my husband was recently a victim when someone tried to take out a loan in his name. Thankfully, the lender turned the thief down and sent my husband a letter explaining the refusal. Good luck with that scam. It felt offensive on two levels: one with the sleazy thief, another with the clueless lender since my husband died five years ago.

T-Mobile just lost their breeches in a hack that compromised 50 million victims’ names, birthdates, social security numbers, and driver’s license information. Whoa, not good! Especially since most consumers offered T-Mobile their highly personal information for a credit check. T-Mobile has downplayed the seriousness of this breach, but this tends to make a company look sketchy in times of consumer need and of big corporation honesty.

It’s not a good look and it may come back to bite them worse that the actual breach itself. Transparency rules!

The T-Mobile hack exposed consumer details which can wind their way back to consumers’ online bank accounts, imperiling all kinds of financial data. Countless false accounts may be opened using the ill-gotten information, unless lenders do an in-depth analysis of consumers applying for loans. Relying on a one-dimensional credit score is not going to expose recent fraudulent accounts.

Shawn Princell, CEO of RIBBIT.ai, talks about his company’s disruptive technology that lenders have been using this past year to propel loan predictability to a new level and guard against fraudulent activity. Princell explains that RIBBIT.ai’s products change the way lenders evaluate consumers, using bank data to connect financial relationships and understand how consumers’ finances have changed over time. Unlike the static credit score, RIBBIT has breathed life into a consumer’s financial lifestyle, offering a more realistic, predictable, and dynamic profile of their ability to borrow and pay back loans.

Steven Thompson, RIBBIT.ai’s Chief Data Scientist says “Our products have been designed to identify fraud and affordability risks from bank account behavior. The advanced technology we pioneered relies on a process we call RevealedAffordability®. This transforms bank transactions and payment processing results into intelligence, including the intent behind the transaction, which more accurately assesses risk and payment outcomes. The depth of the insights, as an adjunct to the lender’s accumulated credit history, helps protect lenders from non-payment outcomes in their lending decisions.”

As the world of shared-data and information grows, so will the skills of the hackers. The T-Mobile hack is a reminder of the importance of smart, multi-dimensional technology that protects lenders and their valuable consumers from adverse loans based on inaccurate information.

 

Stay tuned . . .

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