Detecting Problem Gamblers Using Digital Identity Intelligence

Posted January 28, 2019

Detecting Problem Gamblers Using Digital Identity Intelligence

Solving problem gambling is simple – said no one, ever.

The UK’s love affair, and problem, with gambling is an evolving, complex and at times tragic story that has become more and more intertwined with some of the industry’s biggest brands. Gambling-related stories are now a staple of UK mainstream media. Even members of Parliament are voicing their outrage (between Brexit shouting matches that is).

Approximately half the British population are active gamblers, and about 40% of those players gamble online. Those are phenomenal numbers for any pastime and they are only growing; depending on which report you read, the global online gambling market is set to be worth between $500 billion and $1 trillion by 2022, expanding at a rate of 5% every year.

Two Million at Risk Gamblers

The darker side of these stats: an estimated two million “at-risk” gamblers in the UK alone, with thousands self-excluding every year due to gambling addiction. Young people ages 18-24 are at highest risk, and individual stories of bankruptcy and crime fuelling gambling addiction are everywhere in the papers.

While operators have become gradually more adept at preventing obvious nasties like fraud and financial crime, problem gambling is a whole different animal; when does a big-spender change from a valued customer to a liability? Is it an operator’s responsibility to refuse custom, or the punters to self-regulate?

Responsible Gambling at Board Level

While the industry mulled these questions over, the UK Gambling Commission decided on another route: big scary fines. It’s a blunt, uncompromising approach and it’s been very effective – responsible gambling is now a key agenda item in every operator’s board room. RG Director roles have been created, organizations have been set up and research carried out – all significant strides forward.

But with a recent BBC report exposing serious flaws with the national self-exclusion service, GamStop, questions are being asked about what more could be done to prevent problem gamblers being able to feed their addiction, and whether at-risk players could be detected before disaster hits.

Technology Key

In my conversations with Compliance and Risk Officers at many different operators, the need for effective technology is becoming more apparent. Richard Flint’s (Sky Betting & Gaming Executive Chairman) recent article describes how “…as more and more consumers move online, the best way to protect vulnerable customers is to use data and technology.”

In the end, so much of the challenge lies in correctly and quickly identifying at-risk and self-excluded players. If you can do that, you can take mitigating actions to prevent harm.

Digital Identity Intelligence

Operators track all their players to assess for signs of problem gambling, and GamStop lists self-excluders. But if those problem gambling profiles are linked to a name, email address or phone number, what is to stop a gambling addict from using a fake set of credentials to open a new account and feed their addiction?

When gamblers can evade RG measures as easily as by changing a letter in their name, a fresh approach is needed.

ThreatMetrix has pioneered the use of digital identity intelligence to work out who gamblers are, rather than relying on the credentials they present at onboarding or log-in. This has worked phenomenally well with preventing fraud, and we are now extending those digital intelligence capabilities to problem gambling.

How Does it Work?

A gambler’s RG profile is linked to their ThreatMetrix digital identity, meaning he can be detected even if he uses a different set of credentials to log-in.

ThreatMetrix profiles and links a range of digital fingerprints, including:

  • The device being used to gamble
  • The browser/Operating System being used
  • The location
  • The network router
  • The user behaviour

The log-in credentials being used by the gambler are also profiled, to complete the picture.

Even if a problem gambler uses a totally new set of account credentials, they would be detected by ThreatMetrix as a high-risk player using our range of data points.

The Network Effect

Every event that ThreatMetrix performs is fed into our global network as tokenized data, anonymous and private by design. Every one of our enterprise customers is able to run comparison checks against our network, to work out whether a customer has been seen elsewhere before, and their risk level based on the behaviour they have displayed.

The genius of this is that we are meeting the demand for collaboration in the gambling industry, without operators needing to share sensitive customer data with each other.

The effect of this? Operators are now able to check a brand-new customer against the ThreatMetrix network before they allow them to be onboarded, and make an informed decision whether to accept an individual into their customer base.

ThreatMetrix can be used in this way to detect:

  • Potential Problem Gamblers
  • Self-Excluders
  • Fraudsters
  • Financial Criminals
  • Non-Compliant Access

We all hope to do more to prevent gambling-related harm and to allow people to safely enjoy this fun and exciting pastime. But we need to stop living in the past, using old ways to work out who someone is. We live in the digital age; we need digital age tools for the challenges we are facing today and tomorrow.

Visit us at ICE London 2019 – stand number N9-250 to learn more about how we use global shared intelligence to recognize problem gamblers.

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