Rippleshot
Card fraud shouldn’t be something banks have to shoulder alone. It’s complex, labor intensive and ever-changing as fraudsters’ techniques get faster and more sophisticated. It’s certainly harder when on your own. To help banks proactively detect and fight fraud, Rippleshot created Fraud Forecast™ to empower issuers to optimize their reissuance process, via its flagship product, Sonar. This collaborative tool helps banks fight fraud with data and the power of machine learning.
With over 40 years of experience identifying and mitigating card fraud, Rippleshot saw the problem grow from a transaction-level headache to a weekly news headline. In 2013, Rippleshot took a big-data machine learning approach that is familiar in advertising and search industries, and applied it in a novel way for the payment processing industry. This approach helps banks, merchants, and processors proactively monitor, detect and stop suspicious fraudulent activity, and implement smarter fraud risk management and reissuance strategies when card compromises do occur.