Recent research into gaming machines

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1 30 March 2015 Rt Hon Sajid Javid MP Secretary of State for Culture, Media and Sport 100 Parliament Street London SW1A 2BQ Dear Secretary of State Recent research into gaming machines Section 26 of the Gambling Act 2005 places a duty on the Gambling Commission to provide advice to the Secretary of State on matters relating to gambling and its regulation (whether on request or otherwise). This letter sets out our formal advice on the gaming machines research that the Responsible Gambling Trust published mainly in December The purpose of the research was primarily to improve collective understanding of the scope to identify and address harms arising from gambling on gaming machines in licensed betting shops. The Trust published seven reports in December 2014 and a further report in February The Responsible Gambling Strategy Board, our independent advisory body, submitted its advice on the research in February 2015, and this is attached at Appendix B. Our own detailed advice to you, attached at Appendix A, draws heavily on this. In our view, the research is very useful and takes us forward in a number of ways. It supports the case for more targeted methods of regulating gambling that place more emphasis on the way that players interact with gambling products and environments. In principle, this should improve the prospects for protecting players while allowing the industry to innovate and grow. But there are caveats, and there is some way to go before we can rely on a strategy based on targeted intervention by gambling operators. For any such strategy to be successful, the gambling industry will need to be able to demonstrate that it can identify people at risk of gambling-related harm and then tackle the problem without unduly disrupting play for people who are able to enjoy their gambling responsibly. The research suggests that gambling operators are more likely to identify people at risk where they can build up a picture of a player from a broad range of evidence, including the customer s patterns of play over time. It is hard to do that when the majority of gambling transactions are currently from anonymous play. Moreover, the much richer information that account-based play provides would significantly improve the industry s ability to evaluate its efforts to identify and mitigate risk. Consequently, we recommend encouraging operators to promote account-based play with the aim of increasing uptake significantly. If they succeed, playing anonymously might itself become a useful indicator of risk.

2 If operators fail to make sufficient progress with promoting account-based play, then the case for making it mandatory would need very serious consideration. Society will need to determine where the balance of benefits and costs lies, particularly when some of the issues run much wider than gambling regulation, extending into territory such as personal privacy and freedom to indulge or overindulge. There are also judgements to make around balancing the enjoyment of the many against sometimes severe harm to the few. We will be much better placed to advise on the trade-offs in a year or so as we obtain more evidence, but we would welcome the Department s involvement in and support for building up the cost benefit framework now. In the meantime, our advice is for the industry and the Responsible Gambling Trust to press on with more data analysis to build on the promising early research by developing better models for identifying customers at risk of harm. Further research using the data assembled in the present tranche of reports would be worthwhile, and we think there is value in applying a similar approach to other gambling products and environments, including online. Correctly identifying people who are at risk of harm is only half the story. There is much work to be done on piloting and evaluating actions to then address the identified risk. We would expect the industry to take the lead here, although for any evaluation to be credible it must be conducted objectively and subject to independent challenge. Finally, the bulk of the research was not targeted at questions around stake size. Nevertheless, it has added to our understanding of the issues. While stake size can be a factor in gambling-related harm, the research reinforces our view that interventions focusing on stake size exclusively are unlikely to be effective. We will, as ever, continue to keep you informed of progress. As required by Section 26 of the Act I am sending a copy of this advice to the First Minister in Scotland. Yours sincerely Philip Graf Chair cc: First Minister of Scotland

3 Research into gaming machines Detailed advice from the Gambling Commission March Background 1.1 The Responsible Gambling Trust (the Trust) commissioned a suite of research projects in 2014 largely to begin to answer two questions, as agreed by the Responsible Gambling Strategy Board (RGSB) and the Gambling Commission (the Commission): can we distinguish between harmful and non-harmful gaming machine play? if we can, what measures might limit harmful play without impacting on those who do not exhibit harmful behaviours? 1.2 The Trust published seven reports in December 2014 and a further report in February Appendix C provides a short description of the purpose and key findings of each of the reports. 1.3 Our advice here draws heavily on advice from and discussions with RGSB, our independent advisory body. RGSB s formal advice is at Appendix B. We have also benefited from discussions with Heather Wardle and David Excell, who were key members of the research team. 2 Value of the research 2.1 The value of any research depends critically on its relevance and its quality. In terms of relevance, we intended this research to inform our understanding of some important policy and regulatory policy questions. In particular: how could regulation of products, environment and players be better focused? should the Government revise the current limits on stakes and prizes? should account-based play be mandatory for any or all gambling activities? are there any particular customer protection measures that policymakers and regulators should promote or mandate? what research priorities should policymakers set for the Trust and for the industry more widely? 2.2 Some commentators have cast doubt on the quality of the research. They argue that it is inevitably tainted because the commissioning body includes, albeit as a minority, senior figures from the gambling industry. In our view, the quality of the research depends both on the quality of the data and on the standard of the analysis. The individual reports that make up this programme of research use a variety of data sources and methodologies of varying scale and sophistication. At the heart of the programme is a set of reports that benefit from unprecedented access to extensive data on gaming machine use. These reports linked survey responses from 4,001 loyalty card holders to records of their transactions on machines in licensed betting offices over a ten-month period ending in June The transaction records for these customers included nearly 36 million bets placed. The researchers also analysed unlinked data from a broader sample over the same period, including nearly 6.8 billion bets placed. We are satisfied that the researchers have applied a high standard of independent, objective analysis to this data. The findings come with certain caveats but, interpreted accordingly, we are satisfied that

4 Gambling Commission Research into gaming machines they are sufficiently robust to inform the policy questions above. The bulk of this advice considers the research findings in relation to those questions. 3 How could regulation of products, environment and players be better focused? 3.1 A significant component of existing gambling regulation is focused on characteristics of the product (notably stakes and prizes) and the environment in which the product is available. For example, legislation allows softer forms of gambling in family entertainment centres, which children can access, while harder forms of gambling are restricted to adultonly environments. These restrictions provide some protection for potentially vulnerable people. But there is only so much that they can achieve. 3.2 For any level of restriction on product and environment, short of outright prohibition, vulnerable people will still be at risk of harm as a result of their gambling activity. Our view, informed in large part by advice from RGSB, is that gambling operators can help to protect their customers from harm by responding appropriately to the way that customers interact with their products. In order to succeed, this requires operators to be able to identify those potentially at risk of harm from gambling, for example by identifying play patterns that are characteristic of those at risk, and then to take effective action to prevent or mitigate harm. Identifying patterns of play that indicate harm 3.3 The research provides some support for this approach. It tends to confirm evidence from other jurisdictions that suggests it is possible to use information about individual play to identify players who may be experiencing harm or at risk of experiencing harm. The work is still at an early stage, but some key characteristics of play have emerged that might indicate at-risk individuals. For example, the research confirms and measures the strength of the expected relationship between problem gambling and frequency of play. Operators could make use of these findings now to enhance their responsible gambling programmes. 3.4 There are a number of caveats, however: the work, while genuinely ground-breaking in a UK context, is nevertheless embryonic. And while the researchers have assembled a hugely valuable data resource, the work has focused on one gambling product in one gambling environment. With the time and resources available, the researchers were only able to scratch the surface in terms of interrogating the data. We advise that work should continue to extract the maximum value from this dataset for example, to examine the play patterns and characteristics of known problem gamblers. the predictive power of the models that the researchers developed to identify risk of harm was significantly greater when based on data that linked each customer s information across separate sessions of machine play. Linking data across sessions, however, is clearly hampered by the generally anonymous nature of most land-based gambling. We return to this point below. even the better models still mistakenly identified more non-problem gamblers as problem gamblers for every problem gambler that they correctly identified. In one sense, this might not be too serious. Some of the non-problem gamblers mistakenly identified as problematic might still experience harm as a result of their play, so they might benefit from actions designed to reduce their risk of experiencing harm. Nevertheless, it remains the case that models based on patterns of play are far from perfect. They provide a potentially

5 Gambling Commission Research into gaming machines useful indicator of the risk of harm, but we think that they should form part of a broader toolkit with other indicators. Taking effective action 3.5 Identifying potential problem or at-risk gamblers is only half the story. Once identified, appropriate action is needed in the first instance by the operator to mitigate that risk. The current programme of research was not designed to test the effectiveness of actions in mitigating harm. We are looking to the industry to trial and evaluate different approaches. To help force the pace to that end, last year we consulted on a proposal for the largest gambling operators to submit an annual assurance statement. We are currently consulting on the form and content of these statements, but they will require operators to report on the scale and effectiveness of measures to identify and tackle problematic and at-risk gambling. Senior-level staff would be responsible for signing off the statement, encouraging a socially responsible culture throughout each organisation. We intend to support knowledge sharing so that other operators, including those that we do not require to submit an assurance statement, adopt best practice approaches. 3.6 Conclusion: The research suggests that it is possible to use information about individual play to identify players who may be experiencing harm or who are at risk of experiencing harm. It therefore supports the case for more targeted ways of regulating gambling that place more emphasis on the way that players interact with gambling products and environments. This improves the prospects for protecting players while allowing the industry to innovate and grow. 3.7 But there are some important caveats: the work so far has focused on one gambling product in one environment, and even in that context there is still much to do to develop more reliable tools for identifying harm. even with further development, tools based on patterns of play will be most effective when used as part of a broader toolkit for identifying harm. very little work has been done so far on identifying effective actions to address the risk of harm when it has been identified. for a regulatory strategy based on targeted intervention to be effective, we need to find ways to deal with the inherent commercial incentives for operators to carry on selling their services to individuals who are not in control of their gambling. 4 Should the government revise the current limits on stakes and prizes? 4.1 The research provides a number of observations relevant to questions about stake size. RGSB s advice, attached at appendix 2, provides a detailed account of these observations, which are not repeated here. To highlight the key points: both problem and non-problem gamblers are found at all staking levels. While the proportion of problem gamblers is lower at lower staking levels, it nevertheless follows that larger reductions in stake might be undesirable because they would hit normal leisure gamblers hard while leaving many problem gamblers relatively untouched. while the Trust s analysis has focused on B2 and B3 machines in betting shops, it seems likely, given the strong tendency of problem gamblers to participate in many gambling activities, that a similar distribution would be found in most, if not all, other machine gambling. In this respect, we note that some have sought to use the research to promote a view that gambling problems are somehow only associated with B2 machines in betting shops. Yet we know that problematic gambling is far more closely correlated with

6 Gambling Commission Research into gaming machines frequency and intensity of gambling than with type of product. So, concentrating excessively on one type of product is likely to be counterproductive because it leaves other risk factors unaddressed, whether in betting shops or in other venues. B2 machines in betting shops offer both B2 games and B3 games. While B3 games have a lower maximum stake per game ( 2 as opposed to 100), they are considerably faster, with a typical game cycle of 2.5 seconds compared with 20 seconds for B2 games. And unlike B2 games, which are restricted to betting shops and casinos, B3 games are also found in other gambling environments, including arcades and bingo premises. machine gamblers in betting shops very often combine B2 and B3 games in one session investigating what motivates players to switch between them may provide useful insights to help develop regulatory policy. In the meantime, one potentially significant conclusion is that mean losses in sessions involving only higher stake B2 content were actually slightly lower than mean losses in sessions involving only lower stake B3 content (ie the much faster 2 staking games found in arcades and bingo halls as well as betting shops). the level of mean losses in all session types was quite modest around 6 for single content play, and around 14 for sessions combining B2 and B3 play (where session length was typically greater). However, it is very important to note that discussion of mean values is of limited significance in this area because it is those that play atypically (for more time and or money) who are more likely to be at risk of harm. report 5 1 looks specifically at whether stake size has any impact on players judgement. Based on a small study conducted outside of a real gambling environment, it finds that high stakes may impair the quality of decisionmaking. However, it notes that this finding needs to be replicated in real gambling environments to determine whether the impairment in decisionmaking affects gambling-specific behavioural decisions. 4.2 Conclusion: We know that stake size can be a factor in gambling-related harm. But interventions focusing on stake size exclusively are unlikely to be effective, for two main reasons: large reductions in stake would hit normal leisure gamblers hard while leaving many problem gamblers who stake at lower levels relatively untouched. strategies based on stake size alone might not take full account of the likely response of gamblers. Some might curb excessive expenditure. But some problem gamblers are likely to find other outlets for higher-stake gambling, simply displacing the problem. And for those moving to lower stakes there is likely to be a consequent increase in the amount of time spent gambling, with the associated risk of enhancing its potentially addictive effect. 4.3 These points are relevant, for example, to the current proposal from a coalition of 93 licensing authorities under the Sustainable Communities Act to reduce the maximum stake on B2 machines to 2. The proponents argue that a stake cut to 2 would reduce clustering of betting shops in popular areas and reduce problem gambling and public disorder. We support licensing authorities using their powers to reduce public disorder and improve the local street environment. But cutting stakes is not likely to have much if any impact on gambling-related harm, and the impact on numbers of shops is likely to be muted by problematic gamblers playing longer or moving to other forms of gambling. 1 Understanding of Return to Player messages: Findings from user testing. Collins et al (2014)

7 Gambling Commission Research into gaming machines 5 Should account-based play be mandatory? 5.1 The best algorithms that the researchers developed for identifying risk of harm were based on data from linked sessions of gambling. Linking data between sessions is generally only possible for account-based players and loyalty card holders. But the majority of gambling transactions are currently from anonymous play. Even the most established loyalty card scheme offered by the operators taking part in the research had only a 10% uptake as of February We note that the larger betting operators plan to double uptake of account-based play by June 2015, although this would still leave most machine gambling anonymous. 5.2 So, we can conclude from the research that making account-based play mandatory would probably provide a better basis for identifying players who are at risk of harm from their gambling and for understanding the impact of any measures taken. This would be particularly true of a cross-operator membership scheme, which would enable operators to build a more complete picture where customers gamble with different operators. 5.3 There are a number of other arguments in support of making account-based play mandatory. It could help to: prevent underage gambling support improved systems for self-exclusion from gambling and player protection measures such as pre-commitment (e.g. to limits on amount spent in a given time period) empower consumers by providing them with better information about their play tackle criminal spend. 5.4 But there are also arguments against: we and operators have as yet very little evidence as to how best to use account-based play to minimise the risk of gambling-related harm there are costs to consumers from the additional inconvenience and any restriction on how they play that comes with account-based play. These costs might lead customers to reduce their gambling, whether or not they are at risk, and/or it might tempt them to use unlicensed operators instead the gambling industry would experience an economic impact. This would include the costs of implementing an account based system (including IT and staff training), which would be higher for a cross-operator system. It could also include a reduction in revenue if account based play prompted customers to participate less, and operators would have to deal with uncertainty as to the extent of the reduction there would be implications for civil liberties in terms of privacy and freedom for adults to over-indulge. 5.5 We identified account-based play as an important issue in Strengthening social responsibility, our recent review of social responsibility provisions in our licence conditions and codes of practice. We advised operators that they need to be able to demonstrate how the measures they are taking now, combined with improved use of data available online, support sufficient progress in effective harm prevention and mitigation. As part of their efforts, we would add that operators should consider how best to promote voluntary uptake of account-based play. If the industry cannot demonstrate sufficient progress, then the case for restricting access to anonymous serious gambling may become overwhelming.

8 Gambling Commission Research into gaming machines 5.6 Conclusion: We advise that the time has now come to consider the costs and benefits of removing anonymity, at least for harder gambling. The timetable for the 4th EU Money Laundering Directive, with its likely extension to other sectors of the gambling industry beyond casinos, provides additional impetus for such a debate. The gambling industry must provide evidence of its ability to identify and mitigate the risks of gambling-related harm without restrictions on anonymous play over the next year or so to inform the debate about whether account-based play should be introduced as a precautionary measure. 5.7 Society will need to determine where the balance of benefits and costs lies, particularly when some of the issues run much wider than gambling regulation, extending into territory such as personal privacy and freedom to indulge or overindulge. There are also judgements to make around balancing the enjoyment of the many against sometimes severe harm to the few. We will be much better placed to advise on the trade-offs in a year or so as we obtain more evidence, but we would welcome the Department s involvement in and support for building up the cost benefit framework now. 6 What new measures should we promote or mandate? Voluntary and mandatory alerts and pauses 6.1 The Association of British Bookmaker s (ABB) social responsibility code requires its members to trigger mandatory alerts on B2 machines to players and staff when a customer inputs 250 in cash or plays continuously for 30 minutes. These mandatory alerts provide a safety net for players who choose either to set higher voluntary alert thresholds or not to set any voluntary alerts at all. 6.2 We support the ABB s arrangements for requiring customers to make an active choice about setting voluntary alerts and have recently confirmed that we will make those arrangements compulsory for all licensed betting offices. We then plan to make voluntary alerts more effective by introducing measures to nudge customers into setting more meaningful alert thresholds. 6.3 We also see value in having mandatory alerts as a safety net. But the researchers found that the ABB s mandatory alerts were set too high. In their sample, only 1.3% of problem gamblers would have seen the ABB s alerts. 6.4 In Strengthening social responsibility, we signalled our intention to set lower mandatory alerts in the future. We want to allow sufficient time first to evaluate the impact of other recent measures, including the 50 staking regulation. However, there are two risks with setting excessively low mandatory thresholds for customer alerts: they would disrupt play for non-problem gamblers. they could become overly familiar to players, lessening their impact. 6.5 Our proposal is to strike a balance by setting different thresholds to trigger mandatory alerts to customers and premises staff respectively. Lower thresholds would trigger an alert to premises staff to use their knowledge and judgement to decide whether to interact with the customer. 6.6 We are less clear on the appropriate way forward for pauses in play. Operators both here and in other jurisdictions have used voluntary and mandatory pauses in play to encourage players to consider whether they want to continue to gamble. There is evidence that breaks in play can be effective if initiated by players. But there is informed concern that externally imposed breaks in might in fact result in increased craving (with short breaks

9 Gambling Commission Research into gaming machines creating significantly more craving than no break). This could reinforce habitual behaviours. So, if pauses in play are to continue to feature as a tool to help customers manage their gambling, we will want to see clearer evidence that they have a positive impact. Better information to players 6.7 One of the research reports tested customers understanding of the mandatory messages that each gaming machine must have about the average return it provides to players (the RTP). As we expected, this study revealed that customers generally failed to notice these messages, and that they had a poor understanding of the messages when they did read them. In particular, they failed to understand that RTP results reflect the returns that players could expect to see over hundreds of thousands of repeat plays, and that players could incur significant losses over short periods of intensive play and over more extensive periods of play. 6.8 Although the study was based on evidence from just 25 respondents, and was conducted outside of real gambling environments, it confirmed a view commonly expressed in anecdotal evidence here and in evidence from overseas. We said in Strengthening social responsibility that we will work with industry groups including the Industry Group for Responsible Gambling (IGRG), the Senet Group, and the National Casino Forum (NCF) to find more meaningful forms of information to players. We expect to agree some milestones for this work over the coming months. 6.9 Conclusions: The Commission has recently updated its licence conditions and codes of practice, and the Government s 50 staking regulation will come into effect in April We must evaluate the impact of these new measures before considering additional changes to empower and protect gambling consumers. We expect to see the industry taking the lead in developing and implementing effective social responsibility measures, consistent with licensing objectives, hopefully negating the need for regulatory prescription. 7 What research priorities should be set? 7.1 We think that this research helps to suggest some clear priorities for future work. Generating better algorithms 7.2 We would prioritise further research to extract the maximum value from the dataset assembled for the 2014 research. This should help to generate better predictive models with a wider range of variables. It could include: investigating the patterns of play of the 951 known problem gamblers and 1,025 moderate risk gamblers in the Trust study with a view to reverse engineering indicators of risk not identified in the original study comparing players who switch between B2 and B3 play within the same session with those who stick with one form of play exploring the impact on play of staking with winnings compared with the impact of staking cash that the player has put into the machine. 7.3 We think that exploring this information is likely to be a productive avenue for developing more accurate models. The Trust supports this in principle, and is considering these ideas as part of its future research plans. 7.4 In parallel, we would expect individual operators to develop their own models for identifying potentially harmful patterns of play. Some have already started to do that. Different operators have different customer bases with different characteristics, so attempts to model behaviour are likely to be more accurate if they are operator-specific.

10 Gambling Commission Research into gaming machines We are encouraged that the ABB has established a cross-operator working group to support this work. The group should help to promote knowledge sharing and best practice while still allowing individual operators to tailor their approaches. It must also maintain strong links with the Trust s continuing work, so that operator-specific models capture all the relevant learning from the latest research. Evaluating actions 7.5 Operators are well placed to design and trial actions to tackle harmful play. It is essential that they configure their trials to support robust evaluation. RGSB is developing guidance to help operators to apply best practice evaluation methods, including ensuring that evaluation is conducted objectively. We expect to receive evaluation evidence from the largest operators as part of the annual assurance statements that they will submit to the Commission starting later this year. Developing better measures of gambling-related harm 7.6 Ideally, the researchers would have tested for factors that indicate gambling related harm. But there are no satisfactory ways of identifying harm from gambling. Instead, they used a proxy measure play by loyalty card holders who scored 8 or higher on the PGSI, a screen which relies on players self assessment. This is a reasonable proxy, but it is far from ideal. Problem gamblers don t necessarily experience harm every time they play (and some people who are classified as problem gamblers never experience harm at all). Conversely, non-problem gamblers can experience harm on some occasions. In addition, harm is not normally restricted to the gambler family, friends, employers etc can also be affected. Consequently, we agree with RGSB that it would be worth finding better ways to identify harm from gambling. This approach is likely to involve identifying, classifying and quantifying harms associated with all levels of gambling, irrespective of who incurs them. It might involve, for example, monitoring indicators such as the number of times that gambling is cited as a factor at services including GPs, money advice services, and family/relationship counselling services. In conjunction with RGSB and the Trust, we are considering how this might be done. Further research into contextual information around location 7.7 Report 8 2 seeks to provide some context to machine play characteristics by looking at information on the location of betting offices with gaming machines. Amongst other things, it finds that betting offices with gaming machines are on average more likely to be located in areas of social deprivation although it does not establish any causal link. Separately, our own analysis of data from the health surveys suggests that any correlation might be driven more by the concentration of people who are young, poor or unemployed all risk factors for problem gambling in areas of deprivation. 7.8 The report is essentially exploratory, so its findings have limited immediate value in terms of informing policy directed towards minimising harm. Nevertheless, it might be worth exploring whether the characteristics of regional customer bases vary according to the number of betting offices located in close proximity. If they do, we might begin to understand whether there are particular risks associated with the clustering of betting shops. There could also be value in further work to develop a better understanding of the different commercial drivers for shop location. This could help to inform risk mitigation policies if some drivers however purely commercial their motivation are associated with increased risk to customers. Investigating the characteristics of late night players 7.9 The data reveal an increase in the proportion of 100 stakes after 9pm, although the total number of 100 stakes was actually much lower in the evening than it was during the day. Nevertheless, there should be some value in exploring the differences between late-night 2 A spatial investigation into bookmakers using industry data. Astbury & Thurstain-Goodwin (2015)

11 Gambling Commission Research into gaming machines play and daytime play. For example, evidence of a relationship between alcohol consumption and stake size/losses/problem gambling or between closing time and gambling spend would be relevant to policy around gambling in premises licensed to sell alcohol. Applying similar approaches in other sectors 7.10 We think that the approaches trialled in the machines research should be extended to other gambling products and environments. In this respect we note that the Trust has issued an invitation to tender in relation to similar work on remote gambling data. Investigating the relative harm of different forms of gambling? 7.11 This research has been criticised for not considering whether higher stake machine play is inherently more harmful than other forms of gambling. That was not its purpose. Existing research suggests that certain features, such as speed of play, appear to be associated with increased prevalence of problem gambling, but they are also associated with greater enjoyment of gambling by those not at risk. The intensity of gambling, in terms of time spent and the range of products used, is more strongly linked with problem gambling than any game feature We also know from health survey results that rates of problem gambling amongst those who play on gaming machines are similar to those who play some other activities, such as casino table games and betting on sports events. They are also lower than the rates of problem gambling amongst those who play poker or participate in spread betting. All the indications are that it is the interaction of person, product and environment that matters, not particular features in isolation For these reasons, we do not think that further research into types of gambling products per se is likely to be productive, although clearly we will continue to monitor research in this field for any new insights Conclusion: The recent research has provided a number of valuable insights into gambling on machines, but there is much more to do. We think that work should continue to extract the maximum value from the dataset assembled for the present research. The Trust is considering this as part of its future plans. At the same time, similar approaches could usefully be applied to develop methods for identifying risks in other sectors of the industry. And we are looking to all sectors to do more to evaluate efforts to identify and mitigate harm 8 Overall conclusion 8.1 The Trust s programme of machines research has improved our understanding of machine play and the policy issues that it raises. It does not provide definitive answers for government or regulator, but we had not expected it to do so. It was intended to pave the way, if successful, for better identification of those at risk of harm and for trialling and evaluating ways of preventing and reducing the risk of harm from gambling. Encouragingly, and in line with the overall direction of government and regulatory policy, the research results suggest that the controls on gambling products, and the environments in which they are provided, can be complemented and made more effective with an increased focus on individual players and their specific gambling behaviour. It also highlights the scope for the industry to step up its efforts to develop, trial and evaluate improved harm minimisation measures. Gambling Commission March 2015

12 Keeping gambling fair and safe for all For further information or to register your interest in the Commission please visit our website at: Copies of this document are available in alternative formats on request. Gambling Commission Victoria Square House Victoria Square Birmingham B2 4BP T F E info@gamblingcommission.gov.uk INFO 15/17 10

13 Appendix B MACHINE GAMBLING RESEARCH: ADVICE TO THE GAMBLING COMMISSION FROM THE RESPONSIBLE GAMBLING STRATEGY BOARD Introduction and executive summary 1. The main purpose of the recent set of research projects on machine gambling commissioned by the Responsible Gambling Trust was to begin to answer two questions. These questions were agreed by the Responsible Gambling Strategy Board and the Gambling Commission (the Commission): i. Can we distinguish between harmful and non-harmful gaming machine play? ii. If we can, what measures might limit harmful play without impacting on those who do not exhibit harmful behaviours? 2. The questions have important policy implications. The Commission s contention is that protecting the vulnerable effectively requires more emphasis on how a player interacts with a particular product and not only on product features and the environment in which it is offered. We supported this view in our May 2013 advice on the Triennial Review of Gambling Machine Stakes and Prize Limits. If it is to be successful in the context of machine gambling, the approach requires bookmakers and other operators to be able from data readily available to them to identify potentially harmful play by individual players as it is occurring, and to make effective, tailored interventions in response. 3. Such interventions can be automatic, for example messages on the machine or enforced breaks in play. Or they could require the involvement of members of staff. Some of the former measures are embodied in the Association of British Bookmakers revised voluntary code of conduct and may be incorporated in revisions to the Commission s Licence Conditions and Codes of Practice (LCCP), currently under review. They have not hitherto been rooted in any firm evidence as to their effectiveness. 4. If it turned out that developing an effective way of detecting people experiencing harm through their play was not possible, the effect would be to call aspects of the current approach into question. 5. It is fortunate therefore that the main conclusion of the research is that there are patterns of play that can be used to help identify problem gamblers and potentially those at risk of harm. The predictive power of the algorithms that have so far been

14 developed for in-session play is, however, limited, and based on a highly restricted sample. 6. Predictive power is increased if different sessions of play by the same player can be linked together. But that is possible at present only for players holding loyalty or account cards, and only if those players use their cards when playing. 7. So the outcome of the research is encouraging. But a good deal of further work and piloting is required for it to be successfully operationalised. 8. The research has not so far addressed the second question in paragraph 1. It is necessary to be able to identify harmful play effectively before it is possible to test different interventions designed to mitigate its effects. The next stage of this work requires: i. Further refinement and, hopefully, improvement in the predictive power of the new algorithm in identifying harmful play. ii. A planned programme of piloting and evaluating different interventions designed to reduce harmful play, or to mitigate its effects. iii. Serious consideration of the case for making account-based play mandatory as a way of improving operators ability to detect harmful play, and of the personal privacy, commercial and organisational issues that would be involved. 9. This package of research was directed at the learning which could be extracted from the data made available for the first time by the major bookmakers of actual machine play. Operators had previously regarded such data as commercially sensitive. They are to be commended for providing it to the researchers. 10. The research was not primarily directed at a third, important, question - whether there is something inherent in B2 machine play which makes it a peculiarly addictive and harmful form of gambling. But if this issue is to be looked at objectively it requires some understanding of how players use these machines and of the choices they make. 11. In this context, the research provides some potentially very useful information which helps to inform the concern about high stake limits on B2 machine play and the losses to which users of such machines could in theory be exposed. In particular, the vast majority of losses on B2 machines observed in many million transactions encompassing all plays on machines in the shops of the major bookmakers over a ten month period were less than 10 a session. Substantial losses in a single session are actually quite rare. That said, losses on a relatively small scale can still have a substantial impact on some players and their families, particularly if they are cumulative. 12. Interestingly, it appears that mean losses were actually slightly higher with B3 machine play than with B2 machine play. 13. The key point is that the relationship between stake size and harmful play is not straightforward. There are many factors that may explain why individuals initially

15 choose to gamble, and continue to do so, despite the possibility that they risk or suffer some harm. 14. We suggest that as part of the preparation for the next triennial review of stakes and prizes, due to begin in 2016, it would be helpful to set out what is known about factors that could contribute to a gambling addiction in the context of the new information now available about actual patterns of machine play. Our approach to assessing the research 15. The Responsible Gambling Trust published seven research reports on 1 December, 2014 (see Annex). An eighth will be published shortly. We have seen the final report in draft, before it has been peer-reviewed, and do not believe it has any implications for the advice provided in this paper. 16. On 10 December 2014, Members of the Responsible Gambling Strategy Board attended the Trust s Harm Minimisation Conference, when the research authors gave presentations of their main findings. We also met the following day with the researchers, members of the Trust s Research Committee and Commission representatives to go through the research in more detail and to discuss its potential policy implications. We met again by ourselves on 17 December and finally on 27 January to agree this advice. We have also had the advantage of further exchanges with the researchers on particular points. 17. The following sections review screening for harmful play, stake size and return to players messaging in the light of the research. We conclude with a number of recommendations. Screening for harmful play 18. The first three of the reports address the first question: is it possible to distinguish between harmful and non-harmful play? They need to be considered together. 19. Report 1 identifies a number of plausible markers of harm which might in theory be a positive indicator of harmful play frequency and duration of play, net expenditure, stake sizes, chasing losses and so on. 20. Report 2 identifies a sample of 4,001 loyalty card holders who had gambled on machines in a Licensed Betting Office during the period 1 September 2013 to 30 June of these players were assessed as problem gamblers, defined as scoring 8 or higher on the Problem Gambling Severity Index (PGSI). A further 1,025 were identified as being at moderate risk (scores between 3 and 7). The disproportionately high number of problem gamblers in the sample reflected the selfselecting nature of the sample (i.e. regular players). 21. When loyalty cards are used, every transaction by the holder is recorded to the individual concerned. This makes it possible to track the frequency of machine play and time spent on the machines, and the amounts staked and returned, as long as the individual uses their loyalty card when playing. 1 Report 3 reports the results of testing the potential markers of harm identified in Report 1 to see if by applying them 1 But not, unfortunately, other features which may be accessed during the game a limitation of the data.

16 to the actual patterns of play in the data, singly or in combination, it was possible to distinguish the known problem gamblers in the Report 2 sample from the nonproblem gamblers. A good result would be to be able to identify a high proportion of problem gamblers with as few false positives (i.e. non-problem gamblers identified incorrectly as problem gamblers) and as few false negatives (i.e. problem gamblers who are not picked up) as possible. 22. The researchers summarised their results by using a so-called AUC metric 2. A score on this metric of 0.5 means that the algorithm used to identify problem gamblers is performing no better than would a random guess. A (highly unlikely) score of 1 would indicate perfect results. An algorithm which predicts better than random guesses, but not perfectly, would have a score between 0.5 and 1. Models which generate higher AUC scores are more accurate than those with lower values. Some trade-off between the identification of higher proportions of the target population and the number of false positives is inevitable in any screening process. 23. Use of this approach in relation to gambling is genuinely pioneering. But the research has a number of potentially serious limitations, as the authors recognise. In particular: i. There is an important distinction between harmful play, which may be exhibited in many ways and at many levels, and problem gambling, which is a clinically defined condition. The researchers used play by selected problem gamblers as a proxy, because this was the only information available and because harmful play is not easy to define. In practice, people who test positive for problem gambling may not experience harm every time they play on machines. Conversely, gamblers who are not identified as problem gamblers by their PGSI score may still on occasion display signs of harmful play. ii. Most problem gamblers, and most loyalty card holders, participate in multiple forms of gambling. On average, the participants in the survey had engaged in 4.8 gambling activities (including machine play) in the previous four weeks. So the detection algorithms could only be applied to a proportion of their gambling behaviour. iii. Loyalty card holders do not always use their cards when playing on machines. Only 49 per cent of loyalty card holders identified in the research either always or almost always used their card for machine play. iv. Only about 10 per cent of bets on machines are attributed to loyalty card holders; and loyalty card holders are unlikely to be representative of all gamblers. v. The sample of loyalty card users was highly selective. 3 2 AUC stands for Area Under the Curve. The curve measures the false positive rate delivered by the algorithm corresponding to each true positive rate achieved. A random guess model would produce a curve in the form of a straight line from the point describing 0 per cent true positive/100 per cent false positive to the point describing 100 per cent true positive/0 per cent false positive. Such a line would neatly divide the total area of a graph in half, creating an AUC score of 0.5. A model or algorithm which did better than random guesses would have a bigger area under the curve than above it, scoring more than Of an original population of 131,275 cardholders a process involving criteria designed to concentrate the most likely pool of problem gambling behaviour identified 27,565 individuals. 4,727 of these participated in a survey, of which 4,001 agreed that their survey responses and loyalty card data could be linked. Allowing for cases where the contact details were incorrect, the response rate for the already selective sample was per

17 24. With these caveats in mind, the findings of the research which are most relevant for policy purposes are: i. Focussing on one element of gambling alone, in particular stake size, session length or amount loaded on to a machine, does not provide an effective predictor of problem gambling. In practice, they are only marginally better than random guesses. ii. The recently agreed ABB Code requires warning messages to pop up on machines once a player exceeds 250 of spend or 30 minutes of play. It has yet to be established what effect the messages have on those at risk of harm the group at whom they are targeted. But the research suggests that they will be seen by only a very small proportion of those who are already problem gamblers - 4 per cent after 250, 12.9 per cent after 30 minutes. vi. By combining all the relevant variables, including not only those available by observing only one session of play but also those where it is possible to link sessions of play for individual players, the researchers were able to produce a detection algorithm that is better at identifying problem gamblers than the ABB code thresholds. The most accurate model they were able to produce had an AUC score of That is much better than random. But if operationalised it would still fail to identify a significant number of problem gamblers. vii. The detection algorithm was best at identifying the more extreme problem gamblers, i.e. those with higher PGSI scores. It could accurately identify between 50 and 80 per cent of those with PGSI scores of 19 or more. viii. Unfortunately, linking sessions of machine play in betting shops is only possible where players have loyalty cards, and use them. The best detection algorithm the researchers were able to devise for unregistered play, using only variables relating to a single session of play, had an AUC score of ix. Not surprisingly, problem gamblers who score highly on the PGSI index by virtue of aspects of their behaviour are easier to identify than those who score highly primarily because of the consequences of their behaviour. 25. These figures do not imply enormous predictive power, especially those based solely on single sessions of play. But they may underestimate the value of the model. While many of the false positives thrown up by the detection algorithm may not be problem gamblers as defined by the PGSI index, they may still be at risk players (PGSI scores between 1 and 7). In practice there is a continuum, rather than a clear boundary between harmful and non-harmful play. 26. There are two key issues here. The first is that to be useful operationally a detection algorithm requires a metric that is sufficiently sensitive to identify a significant proportion of those players who score as problem gamblers and those at high risk, while being sufficiently specific to exclude most of those not at risk. The number of problem or at risk gamblers in any randomly selected group of gamblers will always cent, depending on the denominator. Some of the factors involved in the reduction in sample size from 131,275 to 4,727 and then 4,001, like traceability and willingness to participate, may themselves be correlated with behaviour.

18 be small. All but the most sensitive screens will inevitably wrongly capture a large number of non-problem gamblers. 27. The second issue is related. There will be a trade-off between improving a screen s accuracy in identifying problem gamblers and not unreasonably interfering with recreational gamblers enjoyment or operators legitimate commercial expectations. Bear in mind, however, that identification of problem players would not necessarily have to trigger something drastic like a shutdown of the machine. It could simply be first a warning to a player and then an indicator to the operator that some form of intervention should be considered. 28. The significance of the trade-off will depend partly on the nature of the intervention and the context in which it is made. Many will be familiar with other screening devices which occasionally wrongly identify behaviour as aberrant when it is not, for example in relation to potentially fraudulent transactions on credit card accounts. It is probably more irritating to be falsely labelled a problem gambler when you are not than it is, for example, for one of your credit card transactions to be flagged as potentially fraudulent when it is not. On the other hand, a pop up message on a gaming terminal reminding you for how long you have been playing is probably less irritating than trying to pay for a meal in a restaurant for a group of friends and having your credit card refused. Policy implications 29. The researchers in their reports, and the Responsible Gambling Trust in their summary document, claim that the work demonstrates that it is possible to distinguish between harmful and non-harmful play, provided certain trade-offs are regarded as acceptable. 30. That is a strong statement. We should be cautious about accepting it too readily. It would be more accurate to say that the research has shown that it is possible to produce a detection algorithm which is better at identifying problem gamblers than a random guess, and also better than the thresholds used in the ABB Code to stimulate pop up messages to players. But applying the algorithm to in-session play would only produce a percentage point improvement in the identification of problem gamblers compared with the ABB thresholds for the same false positive rate. There is, therefore, some work yet to be done to improve its sensitivity. 31. The detection algorithm performs better when it is possible to link together different sessions of play for the same player. As already noted, however, that is only possible at present for players who hold loyalty cards and who use them a minority of current machine players. 32. The predictive power of the algorithm is much lower than that of many screening tools used in other contexts. The researchers point out, for example, that remote gambling operators have tools available to them which can detect fraud with an AUC score of 0.9 or more. 33. But such comparisons may underestimate the significance of the results. Other effective detection algorithms, such as those used to identify potential credit card fraud or suspicious betting transactions, may have taken years to develop, often have more focused objectives and may be based on considerably more data. The

19 researchers on this occasion had only a matter of weeks to undertake their analysis once the data had been collected. They also tested the usefulness of only a relatively small number of variables. It seems reasonable to expect that with further work the predictive power of the algorithm could be improved, at least to some extent. This might be done by, for example, increasing the number of variables considered, improving their definition or finding a better way to identify harmful play. While widely used, the Problem Gambling Severity Index may not be a very precise tool. 34. Moreover, the algorithm so far developed is better at identifying problem gamblers at the extreme end of the spectrum, presumably those most in need of help; and for harm minimisation purposes it would be advantageous if it identified a large number of at risk players as well as those who are technically described as problem gamblers. 35. Our conclusion is therefore that it is worth pursuing this work further, in an attempt to refine the algorithm so as to increase its predictive power. 36. Despite its current limitations, we also believe that it is worth using the algorithm to pilot the effectiveness of different interventions designed to reduce or prevent harmful play. There is a choice to be made as whether to start these pilots immediately or to wait until the algorithm has been further refined and (hopefully) improved. We suggest that the researchers be asked how substantial an improvement they judge might be possible with a few more months work. In practice it probably makes sense to think of a dual process - refinement of the algorithm and its use in pilots happening simultaneously, with iteration between the two. 37. The design and evaluation of these pilots requires further thought. The summary of the research reports produced by the Responsible Gambling Trust s Machines Research Oversight Panel concludes: It is suggested that at this stage it would be inadvisable to rush policies on the basis of these foundational studies. Rather, consideration needs to be given to the development of a strategic blueprint of evaluative studies that are applied in a logical and coherent manner over the next five to ten years. This is not to suggest a do nothing approach in the meantime. The implication is that more will be achieved by a strategic approach compared to fragmented, disjointed and potentially costly policies that fail to achieve their objective 38. We agree. But we would like to see a more urgent timescale. 39. In the longer run, the fact that the detection algorithm works best when it is possible to link sessions of play 4 strongly suggests that the Government, the Commission and the industry should give further consideration to making account-based play mandatory for all forms of gambling, or at least for machine play. We note that in April 2014 DCMS announced its intention that all larger betting shop operators would be required to offer account based play for B2 machines. 5 This should perhaps be regarded as a useful first step. 4 We assume it would also work better if it were possible to identify more accurately when individual sessions start and end. The researchers had to do that to some extent by imputation, 5 Gambling Protections and Controls (April 2014)

20 40. We recognise that making account-based play mandatory would raise a number of potentially difficult commercial, organisational and personal privacy issues. Until now there has been little appetite to address these issues. We believe that the new research evidence suggests a stronger case for doing so than has hitherto been recognised unless, of course, the industry is able to come up with an alternative way of linking sessions together in the current state of knowledge. The commercial and other considerations need to be balanced against the importance attached to reducing harmful play. Stake size 41. The research was not intended primarily to address the issue of the appropriate maximum stake size for B2 play, at present But the data have nevertheless produced a significant amount of relevant information. In particular: i. Stake size alone has been found by the research to be a poor indicator of play being undertaken by problem gamblers. Problem gamblers are found, albeit at a lower rate, among low stake players as well as those placing larger stakes. ii. Critics of the present maximum stake size have typically placed a lot of emphasis on the total amounts that can theoretically be lost in machine play. Figures of 18,000 an hour have been suggested as arithmetically possible. We pointed out in our Triennial advice to the Commission that such a loss is practically impossible to achieve. It is worth noting, therefore, that the largest single loss identified in 178 million machine gaming sessions all plays on the machines of the five major bookmakers in 8,297 shops over a ten month period - was 13,674. That may seem not far short of 18,000. But it occurred during a session lasting 7.5 hours. 7 iii. There were only 6 other losses of more than 10,000. These are still large amounts. Nor do we know if the losses were incurred by an individual who also made losses in other sessions on other days. But they help put the likelihood of the theoretical maximum loss further in context. iv. The difference between actual losses and theoretical maximum losses is not surprising. Only 3 per cent of sessions involved betting at the maximum 100 stake (though this still implies a large number of sessions in absolute terms, 5.4 million out of 178 million). The mean stake size on sessions involving B2 play only was v. By far the most common game played on B2 content was roulette. The analysis has not looked at how these bets were placed, because the data were not available. If machine players follow the same pattern as players on live roulette tables, however, they will seldom place the whole of their stake on one number which creates only two possible results, win or lose. More typically, they would spread their stake on a set of different outcomes, which 6 There is one partial exception to this. The paper by Parke, Harris, Parke and Goddard (Report 6) records a small laboratory based experiment which suggested that higher stakes may reduce self-regulation by impairing the quality of evaluative processes in decision making. The stakes used were much smaller than 100 (a 20 maximum). The findings have yet to be explored in non-laboratory situations. If confirmed, they would presumably apply to all forms of gambling. 7 It would be interesting to know what if any interventions were made by the betting office staff during this very long session. LCCP social responsibility provision ( Customer interaction ) requires licensees to put into effect policies and procedures for customer interaction where they have concerns that a customer s behaviour may indicate problem gambling.