FICO: 20+ Years of Analytics Innovations to fight Fraud

FICO infographic shows 20+ years of analytics innovations protecting consumers from payments fraud. It highlights the most significant innovations in anti-fraud analytics for card payments, and offers interesting facts about payment fraud.

SAN JOSE, Calif. — March 12, 2014

FICO (NYSE:FICO), a leading predictive analytics and decision management software company, today released an infographic showing how 20+ years of analytics innovations have protected consumers from payments fraud. The infographic tracks the evolution of real-time fraud monitoring for payment cards from its inception in 1992 through today. During that time, for example, payment fraud as a percentage of all credit card transactions in the U.S. has dropped by more than 70 percent. Payment Fraud Informatic FICO infographic highlights the most significant innovations in anti-fraud analytics for card payments, and offers interesting facts about payment fraud in major countries, including France, India, Russia and the UK. The innovations discussed are used in FICO® Falcon® Fraud Manager, which protects 2.5+ billion payment cards worldwide.

  • 1992: Real-time monitoring of credit card purchases by FICO® Falcon® Fraud Manager software utilizing transaction profiles that analyze transaction data to understand behavioral patterns for each account and recognize fraudulent transactions
  • 1993: Neural networks that are simple models of the human brain used to understand complex interactions between variables (e.g., transaction amount, location) to increase precision in identifying fraud
  • 1996: Merchant modeling to spot fraudulent merchant activity
  • 1999: E-commerce fraud modeling to protect merchants from card-not-present fraud by customers transacting on their websites
  • 2004: ID enhancement that strengthens identity fraud detection by using multiple sources of identity-validating data
  • 2006: Modeling of first-party fraud to recognize when people are committing fraud under their own names or invented names
  • 2007: Device profiling that utilizes transaction data associated with devices to detect ATMs under fraud attack on debit card networks
  • 2008: Self-calibrating technology that allows anti-fraud software to fine tune itself in real-time in response to shifts in transaction trends
  • 2010: Adaptive analytics that enable anti-fraud systems to adjust their models on the fly as fraud patterns change
  • 2013: Behavior Sorted Lists that improve the ability to identify suspicious transactions by building comprehensive pictures of each consumer's past behavior

The payment fraud infographic can be viewed and downloaded at