How AI Pegasus Solutions Thwart Real Time Fraud Attacks

Finance

THE CHALLENGE.

The Fight for the Security of Tomorrow Begins Today

A supplement healthcare finance solutions company based in the United States recently was looking for ai solution services company. So they came to Pegasus One with an urgent need to protect its payment processing platform at all costs. Specifically, they were very concerned with brute force attacks by criminals – something that is becoming more and more common all the time. They’d been a victim in the past, and these attacks had resulted in significant network fees for declined transactions They needed an early-warning fraud solution and they needed it now – and luckily, AI Pegasus One was up to the challenge.

How a Rule-Based Solution Thwarts Fraud Attacks and Improves Security Across the Board

Finance

THE CHALLENGE.

The Fight for the Security of Tomorrow Begins Today

A supplement healthcare finance solutions company based in the United States recently came to Pegasus One with an urgent need to protect its payment processing platform at all costs. Specifically, they were very concerned with brute force attacks by criminals – something that is becoming more and more common all the time. They’d been a victim in the past, and these attacks had resulted in significant network fees for declined transactions They needed an early-warning fraud solution and they needed it now – and luckily, Pegasus One was up to the challenge.

APPROACH.

Immediately, our banking and financial services technology team got to work on designing a real-time rule-based ai development solutions that would block stolen credit card numbers immediately, BEFORE someone had a chance to use them. It was designed with self-learning and adaptive artificial intelligence-based solution, thus significantly lowering implementation costs and allowing us to deploy it within months.

If a rule is ever violated, the client’s payment processing platform automatically declines the transaction AND flags the card as an exception – thus allowing stolen cards to be blocked during a brute force attack within few seconds.

RESULTS.

REDUCED FEE

$20K– $25K reduction in network fees

SECURE

1,000+ detected violations per week

Self Learning

Provided insights to continuously develop new rules

After implementation, the client saw an almost immediate reduction in network fees to the tune of $20 to $25 thousand per month. Not only does the solution currently detect more than 1,000 violations per week, but it’s also built to scale as the client’s company does the same. It also uses self-learning technology to provide insights and continuously develop new rules, thus allowing it to become even MORE effective as time goes on.

Above all, it brought much-needed peace of mind to the client by preventing possible future litigations.