FTC takes down Ideal Financial’s fraud network

Patience is a virtue. So is persistence.

Three years ago, the FTC temporarily halted a sophisticated scheme run by Ideal Financial Solutions, Inc. that defrauded millions of consumers out of tens of millions of dollars. Here’s how it worked: The defendants bought consumer payday loan applications, including Social Security numbers and bank account numbers, from data brokers and payday loan websites. Ideal Financial used the information to take money from consumers’ bank accounts — without their OK or even their knowledge. So the court froze the defendants’ assets and appointed a receiver to control the business while awaiting trial.

Fast forward to March 2016: All seven of the defendants — Jared Mosher, Steven Sunyich, Christopher Sunyich, Michael Sunyich, Melissa Sunyich Gardner, Shawn Sunyich, and Kent Brown — are banned from collecting or disclosing consumer account numbers except for transactions specifically authorized by the consumer. The court also banned Ideal Financial’s ringleaders — Jared Mosher, Steven Sunyich, and Christopher Sunyich — from the marketing, sale, and handling of any credit-related products or services. In addition, the court imposed a $43 million judgment for the harm the defendants caused their victims. Kent Brown and Shawn Sunyich separately settled for $25 million in suspended judgments.

The FTC’s case against Ideal Financial led it to two of the data brokers, LeapLab and Sequoia One, that made the fraud possible. The FTC also sued them to stop them from selling consumer identities to other scams.

The lesson for consumers? Think long and hard before you give out your Social Security number or bank or credit card information. Sometimes, you have to, if you want the service or offer. But stop and think: what do you know about the company, their website, or how they’ll protect your information? If you think something has gone amiss with information you’ve already shared, tell the FTC.

This article by the FTC was distributed by the Personal Finance Syndication Network.