February 20, 2018
February 16, 2018
February 15, 2018
The gross win of the gambling market worldwide was forecast to reach about $400 billion in 2015. Gambling is a popular pastime globally. In Australia, over 80 percent of adults are engaged in gambling of some kind. While the majority of gamblers enjoy the thrill and excitement of winning a jackpot, there is an addictive aspect to gaming that is of great concern. Approximately half a million Australians are considered to be at risk of becoming, or already are, problem gamblers.
The negative effects of problem gambling can snowball, touching the lives of many people in the family and wider community through debt and relationship breakdown. The social cost of problem gambling is estimated to be around AU$4.7 billion a year. And it’s a growing concern.
The industry is under increasing pressure to uphold and promote responsible gambling. One of the key successes (that is now being regulated) is a process of self-exclusion for gamblers who are concerned that they have a problem. For this ThreatMetrix client, however, implementing such a system was a difficult undertaking. Addictive behavior is typically hard to break, and gamblers who are savvy with technology have little problem maintaining multiple accounts or identities to allow gambling to continue. This situation is exacerbated by the growth of connected devices and digital access: online gaming is simpler than ever while tracking users has become increasingly more difficult.
The gaming operator needed to find a way to better identify problem gamblers, specifically self-excluders, so their play could be effectively restricted. This wasn’t about just keeping track of their personal details, it was about trying to identify behavioral attributes unique to each player. This meant that if they tried to set up a new account, or access a shared or “borrowed” account, they would be detected and denied.
The challenge for this gaming operator was that it had attempted to use basic personal information to keep track of problem gamblers. It could monitor excluded accounts, but it was difficult to block the self-excluders from gambling if they used a third-party account, or if they opened a shadow account with different credentials.
ThreatMetrix introduced Trust Tags to validate the end user’s true identity, which gave the operator a much clearer view of who its gamblers were, and allowed it to track self-excluders efficiently, regardless of account, presented credentials, or name changes.
ThreatMetrix Trust Tags allowed the operator to “tag” every piece of information it held about a particular gambler, building up a unique digital identity for that person. As well as basic credentials, this might include IP addresses, device specifics, credit cards, email addresses and geolocations. By collecting and maintaining nearly 250 user-specific pieces of information, the operator could identify the gambler with much greater degree of accuracy. If any one of these pieces of information was flagged during a gambling transaction, (for example the same IP address but a different credit card/name), the operator was alerted and could investigate. This allowed it to take an extremely proactive approach to preventing known excluders from re-entering the gambling marketplace.
Since implementation, ThreatMetrix has helped the gaming operator reduce the number of self-excluders slipping through the net to continue gambling by leveraging the following key capabilities: