Rippleshot Blog

Originally Posted Jan 11, 2022 by Northwest Credit Union Association

When it comes to preventing card fraud, issuers need all the help they can get. Fortunately, credit unions have access to a variety of tools, resources, and expertise in their fight against fraudsters’ ever-changing tactics.

Card not present (CNP) fraud is the dominant type of payment fraud that Strategic Link partner CO-OP Financial Services is seeing among its credit unions’ portfolios, comprising over 80% of fraud incidents across both debit and credit.

One key contributor to this rise has been the increasingly bold use of BIN attacks, one of the most common types of CNP fraud.

Originally Posted Oct 4, 2021 by Polly Jean Harrison on The Fintech Times

 n.exchange, a cryptocurrency exchange specialising in fiat on- and off-ramp to make crypto investment user-friendly, unveils its crypto purchase credit card fraud attempt figures for 2019-2021. Its campaign to combat credit card fraud in cryptocurrency highlights a significant rise in fraudulent purchase attempts by cybercriminals using stolen card details, most of which was perpetrated from countries in the Western hemisphere.

Originally Posted Jan 24, 2022 on PYMNTS.com

Originally Posted Jan 8, 2022 by Gordon Kelly on Forbes

Last year saw the biggest hack in iPhone history, complete with individual horror stories from affected users. Now a haunting new discovery could make all iPhone attacks a lot worse.

Originally Posted Jan 21, 2022 by Chuck Brooks

The past two years has seen a rapid shift of work to remote and hybrid offices. The statistics show that hackers welcomed that shift and took advantage of the vulnerabilities and gaps in security by businesses.

Originally Posted Dec 11, 2020 by Alex Rolfe

Nearly half (40%) of merchants are reporting a rise in friendly fraud over the past 12 months, but the majority are struggling to challenge Google Pay and Apple Pay chargebacks successfully, research by Ravelin finds.

Originally Posted Jan 17, 2022 by PYMNTS.com

When you think of a credit union (CU), it’s easy to picture a place that values member relations and face-to-face banking.

While this business model has typically worked to the advantage of CUs, it can also leave some of these institutions ill-prepared for the COVID-fueled shift to digital-first banking — and the risk of online fraud that come with it.

Originally Posted Jan 2022 by GN Feature Story

Banking and financial institutions lose billions of dollars because of fraud. Machine learning can help detect and prevent fraud. 

Machine learning algorithms can reveal fraud patterns much faster and more accurately than humans or traditional rule-based systems. Read this article to understand how exactly banks can benefit from ML-powered solutions in fraud detection.

Each year, banking and financial institutions from all over the world lose many billions of dollars because of fraud. Machine learning seems to be the most efficient technology for detecting and preventing fraud in this rapidly evolving sphere. From this article, you’ll understand how exactly banking and financial institutions can benefit from integrating ML algorithms. Plus, you’ll learn about the shortcomings of traditional fraud detection techniques.