Relying on fraud detection software alone has been found to flag too many legitimate transactions as fraudulent:[1] online purchases are either blocked outright or delayed for review such that the customer abandons the purchase.[2] One approach that has been found successful in reducing the number of "false positives" while still reducing fraud is a "layered" filtering. This technique employs fraud detection software based on algorithms and AI/machine learning, combined with manual review by customer service personnel. Real-time fraud detection supplied by software-as-a-service (SaaS) fraud detection firms includes verifying CVV, PIN/signature, check verification, browser malware detection, address verification, device ID fingerprinting, geolocation, login pattern and success rate[30], authentication by quizzes, cross-checking shared data bases of customer profiles, automated transaction scoring, rules-based filters and other data points.[4]