Our approach to Safer Gambling is based around 4 key principles we have outlined. Here’s how we are keeping these principles front of mind and putting them into practice every day at SBG…

Use of customer data to understand behaviour and monitor for signs of harm

  • Each customers activity is monitored and recorded, with our systems running checks in the background to look for patterns of potentially harmful play. In addition, all our people who have access to this data are trained and encouraged to look for signs of harm.
  • An example of this is to look at customers who have taken the decision to exclude themselves from gambling. We assess data from these customers to look for indicators about what may have triggered this, and to look for clues to how to stop people before their gambling reaches harmful levels.
  • Around 4% of our active player base have ever self-excluded. Through deep analysis of these players, we observed that customers staking at medium and high levels on virtual sports, such as virtual horse racing, were significantly more likely to self-exclude than an average player.
  • As a consequence we have reduced the amount customers are able to stake per bet on this type of product. We are currently analysing the effects of this change on customer behaviour.

We will assess the success of these measures and share what we have learned with industry peers and other interested parties. We continually update our models and algorithms, aiming to improve the efficiency with which we can use data to identify potentially problematic behaviour.

Promote safer gambling by improving the accessibility, awareness and understanding of self-help tools

Over the past year we have significantly increased the prominence of our Safer Gambling tools on our websites, actively marketed these to customers, and also increased our media advertising around Safer Gambling see here.


Since making these changes, we have observed a 111% increase in the number of customers using our cool off tool, a 19% increase in the use of deposit limits, and a 44% reduction in the use of self-exclusion, which we believe is due to at-risk customers adopting controls at an earlier stage than before.

Interact with customers who show signs of harm and discuss their gambling behaviour with them

  • We are starting to use customer data in real time to monitor activity and look for markers of harm, and interact with customers where concerns exist.
  • We are developing new training courses – working with experts from the field of problem gambling treatment – to ensure that our team members are equipped with the skills and knowledge to interact effectively and with sensitivity in what can sometimes be difficult situations.

In the first instance we will use employee feedback systems to understand the extent to which our team members feel confident in their ability to interact with customers.

We will also be analyzing customer behaviour patterns before and after interactions in order to understand effects.

Case study

Our team made contact with a young customer who had previously been suspended due to concerns. Upon being contacted, the customer admitted that his expenditure on gambling had got out of hand and that suspension had helped in re-establishing control. Gambling had also been getting in the way of some of the important things in life -  such as going on holidays with friends – and that he was spending a large proportion of his salary gambling. 

Our decision to reinstate the customer’s account was in recognition of his decision put appropriate controls around his gambling by adopting low-level staking limits. 

Increase our interventions with customers to stop them experiencing harm in the most extreme cases

  • We believe that it is important that customers are empowered to make their own informed choices about gambling, supported by a range of safer gambling tools and controls.
  • However, in certain situations, we accept that we may need to take additional steps to prevent harm.
  • This may include encouraging customers to reconsider bets or engaging with the customer to encourage reflection and abstention.

We will record and track the instances of operator-led measures and undertake research to assess the medium and long term effects of such measures.

Case study

Customer B deposited and bet a large amount on a major sporting event. This represented a significant increase in deposit and stake level compared to their previous betting patterns and so was flagged by our data tracking systems. Our Safer Gambling team had also contacted the customer previously to discuss increases in deposits, with the customer stating that they had been spending more recently and they would now reduce their spending. Following the large bet, a call was made to the customer, who admitted they would be "devastated" if the bet went on to lose.

Our team suggested that the bet was cancelled before the match, but the customer initially wanted to keep it open, and then self-exclude once it was settled. After further discussion, the customer recognised that he would find the consequences of losing this bet damaging and so voided the bet. He also agreed to discuss with our team the benefits of undertaking a period of exclusion from betting and gaming.

The customer subsequently requested a five-year exclusion in recognition of the fact that he was betting beyond his means and was not in full control of his gambling.

And the bet? It would have lost.