Blog Archives
Punter gatherer: What is the role of competitiveness in gambling and problem gambling?
Over the last decade, I have been asked by the mass media on countless occasions about the increasing popularity of online gambling. The two biggest successes appear to be the use of betting exchanges and online poker. Gamblers clearly feel these types of gambling provide value and an opportunity to exercise their skill. This is coupled with increasingly sophisticated gaming software, integrated e-cash systems, increased realism (in the shape of “real” gambling via webcams, or player and dealer avatars) are all inter-linked facilitating factors. However, another factor that I feel is really important in the rise of online gambling is the inter-gambler competition. Obviously there is an overlap between competitiveness and skill but they are certainly not the same. What’s more recent research has suggested that being highly competitive may not necessarily be good for the gambler.
I’m sure many people’s view of psychology is that it is little more than common sense (and to be honest, some of it is). For instance, psychologists claim that male gamblers are attracted to sports betting because they love competitiveness. There has also been North American research examining the high participation in US college basketball. The researchers found that above anything else, males were attracted to the competitiveness of betting on teams and games. Professor Howard Shaffer, a psychologist at Harvard University, claims that men are more likely to develop problematic gambling behaviour because of their conventionally high levels of aggression, impulsivity and competitiveness. Clearly, the idea of the competitiveness of the activity being one of the primary motivations to gamble is well supported.
Based on the fact that so little research has systematically examined the links between gambling and competitiveness, my own research unit published some research into this area in the journal Addiction Research and Theory. Dr. Adrian Parke and myself speculated that a gambler who is highly competitive would experience more arousal and stimulation, and be drawn to gambling as an outlet to release competitive instincts and drives. We also speculated that competitiveness may be linked to problem gambling. For instance, being highly competitive may help in explaining why in the face of negative and damaging consequences, problem gamblers persist in their potentially self-destructive habit. Psychological research in other areas has consistently shown that highly competitive individuals are more sensitive to social comparison with peers regarding their task performance. Applying this to a gambling situation, it is reasonable to suggest that competitive gamblers may be reluctant to stop gambling until they are in a positive state in relation to opposing gamblers, perhaps explaining why excessive gambling can sometimes occur.
Psychology is not the only discipline to suggest that competitiveness levels can be associated with problem gambling. Sociologists have speculated that factors of the human instinctual expressive needs, such as competition, can be temporarily satisfied when engaging in gambling activities. Evidence exists supporting gambling as an instrumental outlet for expressing competitive instinctual urges. The US sociologist Erving Goffman developed what he called the ‘deprivation-compensation’ theory to explain the relationship between gambling and competitiveness. He suggested that the stability of modern society no longer creates situations where competitive instincts are tested. Therefore, gambling is an artificial, self-imposed situation of instability that can be instrumental in creating an opportunity to test competitive capabilities.
In the published research study that we carried out, we hypothesised that problem gamblers would possess higher levels of competitiveness than non-problem gamblers. Using a competitiveness scale, gamblers were asked to rate statements about competitive reasons for gambling (such as ‘I like to gamble to show others how good I am at it’, ‘I like to gamble to beat the system’, ‘I like to gamble to see how good I am at it’) and general competitive tendencies (such as ‘I am competitive’, ‘I enjoy taking risks’, ‘I am abitious’). We found that problem gamblers scored significantly higher on the competitiveness scale. Put simply, we concluded that having a highly competitive streak may in fact be a potential risk factor for problem gambling.
It is not hard to see how a highly competitive person would be attracted to gambling by the competitive and challenging nature of the behaviour. However, why are competitive people at particular risk of developing pathological gambling behaviour? It could be the case that highly competitive gamblers are less inclined to ‘throw the towel in’ or accept a loss, and, as a result are more prone to chasing behaviour. Chasing behaviour – that is, increasing frequency and stake of bets in an attempt to recoup losses – is self-perpetuating. When gamblers chase losses it is highly probable they will lose more and the need to recoup losses increases as time passes. What’s more, chasing losses has been shown to be a major risk factor in the development of gambling problems. At the other end of spectrum, winning is potentially more rewarding for a competitive gambler as they are more inclined to perceive gambling as an internal and external challenge than a non-competitive gambler. In addition, winning will be much more rewarding after incurring losses. Put very simply, the competitive person feels greater triumph by defeating unlikely odds and emerging from what appeared a hopeless situation.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Further reading
Goffman, I. (1972). Where the action is. In: Interaction Ritual (pp.149–270). Allen Lane, London.
Griffiths, M.D. (2010). Gambling addiction on the Internet. In K. Young & C. Nabuco de Abreu (Eds.), Internet Addiction: A Handbook for Evaluation and Treatment (pp. 91-111). New York: Wiley.
Kuss, D.J. & Griffiths, M.D. (2012). Internet gambling behavior. In Z. Yan (Ed.), Encyclopedia of Cyber Behavior (pp.735-753). Pennsylvania: IGI Global.
McCormack. A. & Griffiths, M.D. (2012). What differentiates professional poker players from recreational poker players? A qualitative interview study. International Journal of Mental Health and Addiction, 10, 243-257.
Parke, A. & Griffiths, M.D. (2011). Poker gambling virtual communities: The use of Computer-Mediated Communication to develop cognitive poker gambling skills. International Journal of Cyber Behavior, Psychology and Learning, 1(2), 31-44.
Parke, A., Griffiths, M.D. & Irwing, P. (2004). Personality traits in pathological gambling: Sensation seeking, deferment of gratification and competitiveness as risk factors, Addiction Research and Theory, 12, 201-212.
Parke, A., Griffiths, M., & Parke, J. (2005) Can playing poker be good for you? Poker as a transferable skill. Journal of Gambling Issues, 14.
Recher, J. & Griffiths, M.D. (2012). An exploratory qualitative study of online poker professional players. Social Psychological Review, 14(2), 13-25.
Wood, R.T.A. & Griffiths. M.D. (2008).Why Swedish people play online poker and factors that can increase or decrease trust in poker websites: A qualitative investigation. Journal of Gambling Issues, 21, 80-97.
Risky businesses: Why should employers have a ‘gambling at work’ policy?
Most of us work in organizations that have policies on behaviours such as drinking alcohol and cigarette smoking. However, very few companies have a ‘gambling at work’ policy. One problem gambler in a position of financial trust can bring down a whole organization – Nick Leeson being a case in point when he single-handedly brought down Barings Bank). Leeson’s (albeit somewhat extreme) antics demonstrate that organisations need to acknowledge that gambling with company money can be disastrous for the company if things go horribly wrong. While no company expects an employee gambling to bring about their collapse, Leeson’s case does at least highlight gambling as an issue that companies ought to think about in terms of risk assessment.
Gambling is a popular leisure activity and recent national surveys into gambling participation show that around two-thirds of adults gamble annually and that problem gambling affects just under 1% of the British population. There are a number of socio-demographic factors associated with problem gambling. These included being male, having a parent who was or who has been a problem gambler, being single, and having a low income. Other research shows that those who experience unemployment, poor health, housing, and low educational qualifications have significantly higher rates of problem gambling than the general population.
It is clear that the social and health costs of problem gambling can be large on both an individual and societal level. Personal costs can include irritability, extreme moodiness, problems with personal relationships (including divorce), absenteeism from work, family neglect, and bankruptcy. There can also be adverse health consequences for both the problem gambler and their partner including depression, insomnia, intestinal disorders, migraines, and other stress-related disorders.
For most people, gambling is not a serious problem and in some cases may even be of benefit in team building and/or creating a collegiate atmosphere in the workplace (e.g., National Lottery syndicates, office sweepstakes). However, for those whose gambling starts to become more of a problem, it can affect both the organisation and other work colleagues. Typically problem gambling at work can lead to many negative “warning signs” such as misuse of time, mysterious disappearances, long lunches, late to work, leaving early from work, unusual vacation patterns, unexplained sick leave, internet and telephone misuse, etc. However, new forms of gambling, such as gambling via the internet or mobile phones at work, means that many of these warning signs are unlikely to be picked up. However, just because problem gambling is difficult to spot does not mean that managers should not include it in risk assessments and/or planning procedures. Listed below are some practical steps that can be taken to help minimise the potential problem.
- Take the issue of gambling seriously. Gambling (in all its many forms) has not been viewed as an occupational issue at any serious level. Managers, in conjunction with Human Resources Departments need to ensure they are aware of the issue and the potential risks it can bring to both their employees and the whole organisation. They also need to be aware that for employees who deal with finances, the consequences for the company should that person be a problem gambler can be very great.
- Raise awareness of gambling issues at work. This can be done through e-mail circulation, leaflets, and posters on general notice boards. Most countries (including the UK) have national and /or local gambling agencies that can supply useful educational literature (including posters). Telephone numbers for these organisations can usually be found in most telephone directories.
- Ask employees to be vigilant. Problem gambling at work can have serious repercussions not only for the individual but also for those employees who befriend a problem gambler, and the organisation itself. Fellow staff members need to know the signs and symptoms of problem gambling. Employee behaviours such as asking to borrow money all the time might be indicative of a gambling problem.
- Give employees access to diagnostic gambling checklists. Make sure that any literature or poster within the workplace includes a self-diagnostic checklist so that employees can check themselves to see if they might have (or be developing) a gambling problem.
- Check internet “bookmarks” of your staff. In some jurisdictions across the world, employers can legally access the e-mails and internet content of their employees. One of the easiest checks is to simply look at an employee’s list of “bookmarked” websites. If they are gambling on the internet regularly, internet gambling sites are almost certainly likely to be bookmarked.
- Develop a “Gambling at Work” policy. As mentioned at the start of this blog, many organisations have policies for behaviours such as smoking or drinking alcohol in the workplace. Employers should develop their own gambling policies by liaison between Human Resource Services and local gambling agencies. A risk assessment policy in relation to gambling would also be helpful.
- Give support to identified problem gamblers. Most large organisations have counselling services and other forms of support for employees who find themselves in difficulties. Problem gambling needs to be treated sympathetically (like other more bona fide addictions such as alcoholism). Employee support services must also be educated about the potential problems of workplace gambling.
Problem gambling can clearly be a hidden activity and the growing availability of internet gambling and mobile phone gambling is making it easier to gamble from the workplace. Thankfully, it would appear that for most people, gambling is not a serious problem. For those whose gambling starts to become more of a problem, it can affect both the organisation and other work colleagues (and in extreme cases cause major problems for the company as a whole). Managers clearly need to have their awareness of this issue raised, and once this has happened, they need to raise awareness of the issue among the work force. Gambling is a social issue, a health issue and an occupational issue. Although not high on the list for most employers, the issues highlighted here suggest that it should at least be on the list somewhere.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Further reading
Griffiths, M.D. (2002). Internet gambling in the workplace. In M. Anandarajan & C. Simmers (Eds.). Managing Web Usage in the Workplace: A Social, Ethical and Legal Perspective. pp. 148-167. Hershey, Pennsylvania: Idea Publishing.
Griffiths, M.D. (2002). Occupational health issues concerning Internet use in the workplace. Work and Stress, 16, 283-287.
Griffiths, M.D. (2004). Betting your life on it: Problem gambling has clear health related consequences. British Medical Journal, 329, 1055-1056.
Griffiths, M. D. (2006). Pathological gambling. In T. Plante (Ed.), Abnormal Psychology in the 21st Century (pp. 73-98). New York: Greenwood.
Griffiths, M.D. (2009). Internet gambling in the workplace. Journal of Workplace Learning, 21, 658-670.
Griffiths, M.D. (2010). Internet abuse and internet addiction in the workplace. Journal of Worplace Learning, 7, 463-472.
Griffiths, M.D. (2010). The hidden addiction: Gambling in the workplace. Counselling at Work, 70, 20-23.
Wardle, H., Moody. A., Spence, S., Orford, J., Volberg, R., Jotangia, D., Griffiths, M.D., Hussey, D. & Dobbie, F. (2011). British Gambling Prevalence Survey 2010. London: The Stationery Office.
Loss leaders: What is the best way to measure ‘gambling intensity’?
The issue of how to measure ‘gambling intensity’ is an important one in the gambling studies field. Gambling intensity is one of those concepts that means different things to different researchers but basically refers to how absorbed gamblers are based on the time and money they spend gambling. Over the last few years, this issue has become much more to the fore as researchers in various jurisdictions have been given access to behavioural tracking data (i.e., actual data showing what online gamblers actually do online such as the games they are playing, the time they spend online, the amount of money that they spend, etc.). This has initiated a whole new line of gambling research that is already providing insights about gambling that we never had before.
Many of these studies have used proxy measures for gambling intensity including variables such ‘bet size’ and ‘number of games played’. Another major problem with these studies is that they have tended to present data by single game type (e.g., only data from online poker players or sports bettors are presented). However, as researchers such as myself have noted, online gamblers typically gamble on a variety of games.
There are various ways to conceptualize gambling intensity. Such ways could include parameters involving the time spent gambling, the number of gambles made, and/or the amount of money won or lost while gambling. In almost all of the studies carried out to date, monetary involvement has tended to be the main proxy used measure for gambling intensity. However, I and my colleague Michael Auer have proposed a different proxy measure for the money risked while gambling. We define gambling intensity as the amount of money that players are putting at risk when playing. This might be considered easy to do (e.g., by using ‘bet size’), but the element of chance is rarely accounted for, especially when a random win occurs. For instance, two gamblers putting the same amount of money at risk might end up with very different wins or losses at the end of similar length gambling sessions because of the chance factor. For this reason, we are now using a measure that is completely independent of random events and takes into account the true amount of money that players are prepared to risk. The interesting aspect of this is that most of the time, gamblers themselves are probably not aware of the amount of money they risked at the end of a playing session.
Our first published paper in this area was a simulation study published last year in the journal Gaming Law Review and Economics. In that paper, we demonstrated that the most robust and stable measure for ‘gambling intensity’ is what we call the ‘theoretical loss’. Our fiest paper on this topic showed that all previous studies using proxy measures for ‘gambling intensity’ had failed to take into account the house advantage. Outcomes in games of chance over the long-term will always be dependent upon the house advantage of each different type of game. Dr. S. Li showed in a 2003 paper published in the Journal of Risk Research that ‘at risk’ decision-making in the short-term is totally different from decision-making over longer periods of time. Decision making over the long-term can be explained by the expected value whereas short-term decision-making does not seem to be based on any expectation rule. However, studies investigating decision-making in situations where people have to make choices assume that players have a real choice in which they can truly influence the outcome and (thus) the expected return. However, this is not the case in pure chance games. Whatever the player chooses to do in pure chance situations, the house advantage will determine the expected return in the long-term.
As we pointed out in our 2012 paper, games with a high house advantage lead to higher player losses and games with a low house advantage lead to lower player losses. Theoretical loss is the same measure that the gaming industry describes as Gross Gaming Revenue (GGR), and is the difference between ‘Total Bet’ and ‘Total Win’. The ‘theoretical loss’ of any given game is represented by the product of the bet size and the house advantage. Over very long periods of time, the theoretical loss corresponds to the GGR with increasing accuracy. The more diverse the gambling behaviour, the more that bet size deviates from the theoretical loss.
By incorporating the theoretical loss, the amount risked can be measured at a very detailed level. For instance, French roulette has a house advantage of 2.7% and keno has a house advantage of 10%. This means that a player who repeatedly bets $100 on roulette will end up with a loss of $2.7, and a player who repeatedly bets $100 on keno will end up with a loss of $10. Therefore, the product of bet size and theoretical loss represents the amount of money that player will lose in the long run. Previous studies that have used bet size (as a proxy measure for gambling intensity) would assign the same gambling of $10 intensity to the two players in the aforementioned example (and which obviously is not the case). The bet size is the one risk parameter that players are most likely to be aware of during gambling. However, it is deceptive as it does not take into account the expected return/loss that is controlled by the gaming operator via their house advantage.
Our simulation study of 300,000 online gamblers showed that bet size explained only 56% of the variance of the theoretical loss, and the number of games played explained 32% of the variance of theoretical loss. This means that when using bet size alone, 44% of the gambling behaviour remains unexplained. When using the number of games played alone, 68% of the variance is left unexplained. As this study was a simulation, we recently replicated our first study using real online gambler behavioural tracking data. There are many advantages and disadvantages with using data collected via behavioural tracking. However, the main advantages are that behavioural tracking data (a) provide a totally objective record of an individual’s gambling behaviour on a particular online gambling website, (b) provide a record of events and can be revisited after the event itself has finished, and (c) usually comprise very large sample sizes.
Our latest study on theoretical loss in the Journal of Gambling Studies comprised 100,000 online gamblers who played casino, lottery or poker games during a one-month period on the Austrian win2day gambling website. All games played by these gamblers were recorded and subsequently analysed. The game types were categorized into eight distinct groups: (i) Lottery – Draw/Instant, (ii) Casino – Card, (iii) Casino – Slot, (iv) Casino – Videopoker, (v) Casino – Table, (vi) Casino Other, (vii) Bingo and (viii) Poker. For each of the game types and each player, the ‘bet size’ and the ‘theoretical loss’ were computed for the recorded time period. In terms of house advantage these game types are very different. In general, lottery games have a relatively high house advantages (typically 50%) whereas slot machines have house advantages in the range of 1 to 5% depending on the gaming platform and the specific game. Poker on the other hand does not have a house advantage as such. In poker, the gaming involvement can be measured via the rake. The rake is a fixed percentage of the stake (bet size) that goes to the casino. The overall theoretical loss is thus comprised of the theoretical loss across all game types plus the poker rake.
Although we found a high correlation between the ‘bet size’ and the overall ‘theoretical loss’ across the eight game types for the 100,000 players, we also found the bet size alone explained only 72% of the variance of the theoretical loss (not as large as we found in our simulation study but that was most likely because we had more games in the simulation study and the games in the simulation study were approximated house advantages whereas the follow-up study used actual house advantages.
This study broadly confirmed the findings from our previous simulation study. The results of our most recent study suggest that future research and particularly those that utilize behavioural tracking approaches should measure their participants’ gambling intensity by incorporating the game-specific theoretical loss instead of using proxy measures such the bet size and/or the amount of money staked. Another implication is that previously published research could be re-analysed using the more robust measure of gambling intensity presented here (i.e., theoretical loss) rather than the proxy measures that were used in the original published studies. This study demonstrates that bet size does not reliably indicate the amount of money that players are willing to risk as it does not take into account the house advantage of each individual game that gamblers engage in. The house advantage represents the percentage held back by the gaming operator and is essential for the amount lost in the long-term and will eventually be equal to the total losses that a player accumulates. In order to further generalize our results, further empirical research utilizing data from other online gaming platforms as well as land-based casino premises needs to be carried out.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Additional input: Michael Auer
Further reading
Auer, M. & Griffiths, M.D. (2013). An empirical investigation of theoretical loss and gambling intensity. Journal of Gambling Studies, in press.
Auer, M., Schneeberger, A., & Griffiths, M.D. (2012). Theoretical loss and gambling intensity: A simulation study. Gaming Law Review and Economics, 16, 269-273.
Broda, A., LaPlante, D. A., Nelson, S. E., LaBrie, R. A., Bosworth, L. B. & Shaffer, H. J. (2008). Virtual harm reduction efforts for Internet gambling: effects of deposit limits on actual Internet sports gambling behaviour. Harm Reduction Journal, 5, 27.
Colbert, G., Murray, D., Nieschwietz, R. (2009). The use of expected value in pricing judgements. Journal of Risk Research, 12, 199-208.
Griffiths, M.D. & Auer, M. (2011). Online versus offline gambling: Methodological considerations in empirical gambling research. Casino and Gaming International, 7(3), 45-48.
Griffiths, M.D. & Whitty, M.W. (2010). Online behavioural tracking in Internet gambling research: Ethical and methodological issues. International Journal of Internet Research Ethics, 3, 104-117.
LaBrie, R.A., Kaplan, S., LaPlante, D.A., Nelson, S.E., & Shaffer, H.J. (2008). Inside the virtual casino: A prospective longitudinal study of Internet casino gambling. European Journal of Public Health, 18, 410-416
LaPlante, D. A., Schumann, A., LaBrie, R. A., & Shaffer, H. J. (2008). Population trends in Internet sports gambling. Computers in Human Behavior, 24, 2399–2414.
Li, S. (2003). The role of Expected Value illustrated in decision-making under risk: Single-play vs multiple-play. Journal of Risk Research, 6, 113-124.
Wardle, H., Moody, A., Griffiths, M.D., Orford, J. & and Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: Evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11, 339-356.
Scam-a-lot: A brief look at online gambling fraud
I’m sure many of you reading this have received bogus e-mails notifying them they have won a lottery. The majority of these scams are either the ‘Dutch Lottery’, ‘Spanish Lottery’ and ‘Canadian Lottery’ schemes (although there are many others). The theme is always the same and they appear to make a lot of money for those that instigate the scam. According to press reports a few years ago, the Canadian Lottery scam netted over $5 billion from US victims and was making around £500,000 a month in the UK. Typically, a person receives an e-mail saying that they have won a lottery and they need to reply to claim their winnings. If the person replies, they will then receive emails and/or phone calls that move the person on to the next phase of the fraud. The person will be told that they need to pay a fee – which can be variable – to cover transfer and administration costs (sometimes termed an ‘unlocking fee’). Sometimes the fraudsters ask for a person’s bank details so that they can deposit the winnings. When this happens, the fraudsters can also steal money directly from a person’s account. The obvious reason why such e-mails are fraudulent is that the person has not bought a lottery ticket. However, frausdsters have started to use slightly different tactics. Below is an extract from an e-mail that I received in my inbox:
“We are pleased to inform you of the result of the Lottery Winners International programs held on the 14th of January. You have therefore been approved a sum pay out of US $500,000. CONGRATULATIONS!!! Due to mix up of some numbers and names, we ask that you keep your winning information very confidential until your claim has been processed and your prize/money remitted to you. This is part of our security protocol to avoid double claiming and unwarranted abuse of this program by some participants. All participants were selected through a computer ballot system drawn from over 200,000,000 company and 300,000,000 individual email addresses and names from all over the world”
Here, the person appears to have had their e-mail address randomly selected into a prize draw (rather than having to have bought a ticket). To claim the prize, recipients of the e-mail are again asked to pay an administration fee. One of the more worrying aspects is that those people who have responded to these types of schemes and frauds before will find themselves named on “mooch” and “sucker” lists that are sold by specialist brokers to the fraudsters. If a person has been duped once, they will almost certainly be targeted again.
Frauds rely on gullibility of the victim and the credibility of the criminal engaging in the fraudulent activity. On the Internet, this might perhaps translate into having very state-of-the-art webpage forgeries on the Internet with credible and trustworthy sounding materials/products. One of the most common fraudulent practices is when unscrupulous individuals steal materials from legitimate online gambling sites. Whole website designs can be stolen including the graphics and general design. Others may just use accreditation logos from legitimate accreditation organizations such as GamCare or the Internet Gambling Commission. Such people rely on the fact that many gamblers have made the decision to gamble even before logging on. The urge and desire to gamble can help overcome a person’s ability to think rationally and/or their instinctive mistrust of the Internet. Fake sites have to look safe, reputable, and trustworthy. To avoid spending money on website design and development, the fraudsters simply steal existing designs. Some fake sites even go as far as making identical copies of winners’ pages and testimonial pages of legitimate sites. This reinforces the idea that the site has hundreds of happy and satisfied customers. Only those who are intimately familiar with the “host” or original site would notice such a fraud.
Many online gambling sites offer incentives to get the gambler to play on their site. These include legitimate schemes such as VIP membership, loyalty schemes, and various types of deposit bonuses (i.e., the gamblers get a cash bonus if they register with the site). One of the legal (but highly exploitative) ploys to get people to gamble, are those sites which require excessive play (or to have gambled a pre-set amount of money) before the cash bonus is awarded. However, there are some ‘bonus’ practices that go beyond exploitation and are clearly fraudulent. One of the simplest, and most effective of the bonus scams is targeted at players that have been banned from a casino. Since online casinos are always in need of known paying customers, this works by drawing in banned gamblers who have moved on to other sites. The gamblers receive an e-mail offering them a cash bonus if they deposit money into their existing account. However, after the gambler has deposited the money, they do not get their bonus. The online casinos tell the player they are not eligible to receive a bonus because they were banned. Gamblers then tend to play their deposit anyway – which is exactly what the operators were hoping for. Furthermore, some online casinos cite ‘bonus abuse’ as the reason for not paying winnings, knowing there is no governing body that can act against them.
Another unscrupulous tactic is where online gambling sites that have conned a gambler once, do it again (a “two-for-one” scam). If a gambler has signed up to a particular online casino that takes all their money and then disappears, there is little a gambler can do. Quite often, months after being ripped off, a gambler may start to get e-mails from a new gambling site set up by the fraudsters who conned the gambler in the first place (although the gambler is unlikely to know it is the same organisation). They know where to reach the gambler because of the registration form that the gambler initially filled out to join the now disbanded online casino. The fraudsters will e-mail compelling offers, rewards packages, and CD software (basically anything to get the gambler back). The fraudsters then do exactly the same again. Another variation of the ‘twofer’ scam is when gambling operators invite their former scammed customers (by using the information the gambler provided before at a previous site) under the ruse of ‘bonuses’ telling the gamblers how sympathetic they are about them being scammed, and offering a bonus if they play on their website instead.
There appears to be one major reason why gambling is such a growth area for fraud. This is the fact that many gamblers themselves want to get a huge reward from a small outlay (just as the fraudsters do). As long as there are people who are prepared to risk money on chance events, there will be those out there who will want to fraudulently take their money from them. To date, there is almost no empirical data on any of these criminal practices and it is hard to assess the extent to how widespread any of these fraudulent online gambling practices are. There is clearly a need to examine this area empirically and for research to be initiated in this emerging area of criminological concern.
Dr Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK
Further reading
Griffiths, M.D. (2003). Dot cons: Exploitation and Fraud on the Internet (Part 2). The Criminal Lawyer, 134, 3-5.
Griffiths, M.D. (2003). Exploitation and fraud on the Internet: Some common practices, The Criminal Lawyer, 132, 5-7.
Griffiths, M.D. (2004). Hi-tech gambling scams. The Criminal Lawyer, 140, 4-5.
Griffiths, M.D. (2008). Online trust and Internet gambling. World Online Gambling Law Report, 8(4), 14-16.
Griffiths, M.D. (2010). Crime and gambling: A brief overview of gambling fraud on the Internet. Internet Journal of Criminology. Located at: http://www.internetjournalofcriminology.com/Griffiths_%20Gambling_Fraud_Jan_2010.pdf
Griffiths, M.D. & Wood, R.T.A. (2008). Gambling loyalty schemes: Treading a fine line? Casino and Gaming International, 4(2), 105-108.
McMullan, J. & Rege, A. (2007). Cyberextortion at online gambling sites: Criminal organization and legal challenges. Gaming Law Review, 11, 648-665.
Whitty, M. & Joinson, A. (2009). Truth, Lies and Trust on The Internet. Hove: Routledge.
