he Featurespace software enables protection by automatically spotting and detecting activity designed to simulate that of humans, but is actually generated by computer software. Its system is able to automatically discriminate between genuine players and computer-generated bots by learning the characteristics of human interaction to detect anomalous behavioural patterns and to block any spurious access.
King.com is an active supporter of consumer privacy and protection and this is the latest proactive step it has taken to protect its more than 17.5 million unique users that play each month.
The software developer already has signed deals with King.com to guard the firm's online skill games, and both Internet poker and online casino operators are eager to employ the product to prevent cheating. Betfair has already reached an agreement, and other online gaming companies are lining up to ink deals.
Software analysis searches for abnormal betting patterns, and then groups them into those choices that reward the player and those that don't. The system is able to tell when fraudulent play at online gambling is happening, and whether the choices are being made by a human or computer bot.
The need for greater detection methods of online gambling fraud and cheating was borne out by last year's scandal at online poker rooms Absolute Bet and Ultimate Poker. Crooked play was eventually detected, but only after months of intensive human investigation.
"King.com's market leadership is based on both the quality and the integrity of our games," said Riccardo Zacconi, CEO of King.com. "By being the first skill games company to deploy Featurespace's system, we are protecting our players and ensuring that they are in fact playing against real people."
Featurespace supplies behavioural analytics software for a range of applications including the detection of online fraud and the identification of high value online customers. The company was founded in 2005 and builds on pioneering behavioural pattern recognition research undertaken at Cambridge University.
Featurespace's approach involves the statistical analysis of human online data patterns, and delivers deep insights into online customers' motivations and preferences.