FICO, an analytic software firm, has rolled out its new payment card fraud detection models to make card-not-present (CNP) transactions more convenient and secure.

The California-based company said that its new Falcon consortium models for payment card fraud detection comprises machine learning technology, which enhances card-not-present (CNP) fraud detection by 30%.

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Besides decreasing the CNP transaction review rates without increasing fraud risk, the new tool doubles the detection of fraudulent, high-value CNP transactions on the first attempted transaction.

The Falcon consortium, a pool of anonymised transaction details gathered from 9,000 financial institutions worldwide, enables FICO data scientists to examine and prove the performance of new models prior to release.

The new models, which have been developed based on analysis of over four billion transactions, can considerably reduces CNP fraud losses without increasing false positive rates.

At the outset, the new Falcon consortium models for both credit and debit cards will be available for FICO Falcon Platform customers in the UK and Europe later this year and then to customers in other markets across the globe.

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FICO vice president for fraud solutions TJ Horan said: “Consumer convenience is driving rapid growth in online transactions. As a result, criminals are looking to use this convenience to their advantage as chip cards and other security features have made physical card fraud more difficult.

“Our goal is to help card issuers promote a positive consumer experience while protecting them from financial harm. These CNP machine learning innovations are important tools to help issuers spot fraud faster, and take on even greater importance in the light of recent data breaches, which will lead to more fraud attempts.”