Automated Card Compromise Detection Platform



Sonar from Rippleshot enables card issuers to monitor and manage data compromises, reducing bank fraud losses and costly card re-issuances.  By leveraging big data analytics, Sonar’s technology determines the common point of purchase among compromised cards, ranks cardholders by risk level, and generates automated rule suggestions to shut down fraud quickly with fewer false positives. Learn more.
ABA Members receive 15% off the ABA-endorsed fraud detection solution for debit, credit, and prepaid card issuers.


 

 Key Features

 
  • Automation: No home-grown spreadsheets. No manual list uploading. Sonar analyzes your entire card portfolio nightly, bringing you fresh new information to take action on each morning.
  • Tokenization: All transaction data is tokenized and scrubbed of PII before being uploaded to Rippleshot’s Analytical Cloud.
  • Whales & Minnows Approach: Sonar identifies data compromises that involve dozens or even thousands of cards, picking up on compromises that card networks often don’t have time to investigate.
  • CP & CNP Transactions: Sonar considers the need for a combined approach to cover both CP and CNP types of fraud.
  • Fraud Forecast: Determine which cards in your portfolio are truly at risk with an individualized percentage of how likely each one is to go fraudulent in the next 90 days. Learn more and get a demo.
  • Portfolio Agnostic: Credit, debit and prepaid cards are all at risk for fraud. All three portfolios can be analyzed using Sonar.
  • Smart Rule Suggestions: Sonar’s compromise detection gets combined with other fraud variables for regularly updated custom-designed decline rule suggestions that meet or exceed your current FPR.
  • Consortium Model: Sonar detection gets faster the bigger the data set gets, meaning all clients benefit from the data consortium and model adjustments without the need for version releases or new purchases.

 

 Program Benefits

 
  • Faster CPP identification. Sonar's common point of purchase (CPP) identification is faster than any traditional method of detection on the market today. In the case of Home Depot, Sonar detected the breach more than 100 days before the public announcement.
  • Facilitates better use of resources. Bankers spend significantly less time tracking down CPPs. Resources can be more effectively allocated toward fraud mitigation.
  • Enhances bank profitability. Sonar's built-in functionality provides smart rule suggestions for your portfolio to help you capture more fraud while keeping customers happily spending. Banks employing Sonar rules have seen up to a 400% lift in the amount of fraud captured while lowering false positives.​
 

 Rippleshot Press

 
  • American Banker - “ [Rippleshot] Collects data from card issuer clients and pores through card transactions to find signs of fraudulent behavior, often by looking at past illicit activity and comparing it to current behavior. It zeros in on specific merchant locations to find trouble spots.” 
  • Crain’s Chicago Business - “Tran and his team developed an algorithm that determines the common point of purchase among compromised cards. Rippleshot's portal then sends out alerts so clients—banks, credit unions and retailers—can shut fraud down quickly.” 
  • The Nilson Report - “Rippleshot statistical analytics and machine learning can distinguish between the actual data breach and any nearby stores that get payments from the same cardholders. This lets them provide assessments with significantly fewer false positives.”
  • PYMNTS.com - “Rippleshot entered a market where cybercrime was about to become an ominously familiar household word. And though no one likes thinking about it, being aware is proven time and again as the best method for warding it off.” 

​​Questions? Please contact Jackie Lucas for more information.



 

 News and Insights

 
​The Equifax Breach
The Equifax breach highlights a rapidly growing threat to banks: the rise of synthetic fraud. Just how big of a threat is synthetic fraud? This $6 billion annual problem creates an average fraud loss per account of $15,000. In fact, one bank suffered a $60 million loss from synthetic fraud. In another case, a fraud ring was responsible in $200 million in losses alone. That's just the tip of the iceberg. Read Rippleshot's blog post ​Equifax Data Breach: The Long-Term Impact on Fighting Fraud.

The Impact of Fraud on Card Growth
As consumer card transactions are primed to overtake cash transactions for the first time in 2016, Bank Innovation speaks with Rippleshot on the impact of fraud on card growth. Read "Card Fraud Reaches New Heights, and So Does Fraud."

Hotspots for Credit Card Fraudsters in Texas
The Dallas Business Journal recently ran an article featuring Rippleshot’s CEO Canh Tran that discusses why grocery stores and banks are hotspots for credit card fraudsters in Texas. The article also includes a visual slide show of typical places fraudulent credit is spent by fraudsters in the state. Read “Where Credit Card Fraudsters Like to Shop in Texas and Why.”
 

 Past Webinars

 
How Exactly Are Fraudsters Ripping Off My ATM?
Download the recording.

The State of Card Fraud: Are You Ready for the Holiday Season?
Download the recording.

The Future of Card Data Security and Fraud Prevention​
Download the recording.​
 

 Blog Posts

 
 

 Program Contacts

 
ABA Contact
Robin Gordon, (202) 663-5128​

Rippleshot
321 N. Clark Street Suite 2550
Chicago, IL 60654
888-407-3025