Bet Buddy wins significant R&D investment from the UK Technology Strategy Board

Bet Buddy, the innovative and award-winning gaming analytics business has recently won approval for significant R&D funding from the Technology Strategy Board. The funding will support pioneering development work, leveraging City University's academic skills to further machine-learning driven consumer protection techniques.

Bet Buddy provides advanced analytics solutions to the gaming industry, helping gaming companies to better understand and interpret player behaviours, and also to better manage problem gamblers.

In conjunction with City University London's Machine Learning Group, Bet Buddy led a proposal to research advanced techniques in consumer protection and related business domains. The project combines Bet Buddy's proven models and real-world capability to deliver meaningful business services to the gaming industry with City's leading-edge machine-learning research, specifically the use of deep learning models.

The Technology Strategy Board - the UK's 'innovation agency' - is a body established by government to drive economic growth by stimulating and supporting business-led innovation.

Founder and CEO of Bet Buddy, Simo Dragicevic, noted,

'TSB support for this project is invaluable. Whilst we have the market-leading solution for responsible gaming, at the heart of data science is the concept of continuous improvement, and that applies to our products too. Combining the latest academic research into machine-learning with Bet Buddy's proven service and analytic approaches will drive the development, availability and quality of next-generation real-time behavioural analytic solutions across a growing number of sectors'.

International Centre for Youth Gambling: Behavioral Analytics Article

Bet Buddy has published an article in the latest newsletter of the International Centre for Youth Gambling Problems and High-Risk Behaviours (Fall 2013, Volume 13, Issue 3). The centre is a McGill University Research Centre that is focused on research, prevention, and the training of researchers and professionals concerned with youth gambling and treatment. The article describes the principles and applications of behavioral analytics technology in gaming, discussing how researchers such as the Division on Addiction and gaming organisations, such as Bet Buddy and GTECH, have built an evidence base for by using player data was the study of actual internet player gambling data. The article then explains how this is evidence is now being used by Bet Buddy to enable lotteries and commercial operators to better protect at-risk players through the use of Bet Buddy's technology. We would also like to take the time to congratulate Dr. Jeffrey Derevensky, Founder and Director at the Centre, on winning the 2013 NCRG Scientific Achievement Award, a thoroughly deserved award!

What does the analysis of internet casino gambling player data tell us about behaviour and risk?

Our research analysing internet casino data has now been published in the latest edition of International Gambling Studies (Vol. 11, No.3), a special edition on Internet Gambling. The paper outlines the phase 1 findings from research undertaken by Bet Buddy in partnership with GTECH and City University London which utilised anonymised player data from a research cohort of 128,788 players from three internet gambling sites licensed in Malta offering internet casino and poker to regulated markets. Whilst the research builds on the methodology adopted by the Harvard Medical School and bwin Interactive Entertainment AG (specifically Braverman and Shaffer (2010)), which analysed live action sports betting internet data relative to gambling risk factors using k-means clustering analysis, our research explores the casino results in new contexts not covered in previous research. To the best of our knowledge this research, along with the Harvard/bwin collaboration (an overview of the collaboration can be found here), is the only peer-reviewed research to be published that analyses actual internet gambling data, and is the only research to analyse casino internet gambling data in the context of risk.

Whilst we discussed some early insights from the research in a previous blog this paper contains the full results and analysis. Our results are analysed in the context of risk factors, game structure, player education and clinical models for problem gambling. For example, we suggest that the analysis of some risk factors, such as loss chasing, could prove problematic when using current gambling screens (such as DSM-IV) in the context of internet gambling. Our results showed that real active money gamblers with the highest intensity and frequency levels gambled predominantly on slots type casino games, in comparison to the most moderate gamblers who preferred table games. We also examined how behavioural analysis and feedback mechanisms can help players to regulate gambling behaviour (for example how medical data is being used to help people make more informed choices - see this TED video). We explore how the opportunities that data analysis offers can help move beyond the traditional applications of data analytics in the gambling industry such as in marketing and risk management, in that applying advanced data analysis in new contexts (e.g. healthcare) can identify individuals who would benefit from proactive intervention or lifestyle changes (McKinsey's Big Data report discusses the application of data analytics in industry in general in greater detail). When the results were analysed in the context of clinical models for pathological and problem gambling (such as the Pathways Model) we found certain limitations. For example, we would have benefited from augmenting our existing internet gambling data sets with new data sets, such as call centre data, which can also be used to help predict gambling behaviours (see Haefeli, J., Lischer, S., & Schwarz, J.(2011)). 

We believe that this research is an important step in furthering our understanding of internet gambling behaviours in the context of risk and player protection and welcome feedback from industry and academic practitioners. If you interested in finding out more about our research and product offerings then please contact us.

Show Us the Data (It’s Ours, After All)

An interesting article by Richard Thaler, professor of economics at Chicago Booth Graduate School of Business, makes the case why consumers should own their ever growing personal data generated as a result of digital social and commercial interactions.  Data is big business.  Why?  Because sophisticated organisations who can accumulate and mine data use it to generate insights, and ultimately sales.  But whilst organisations invest heavily is using data to drive sales, Thaler focuses on the consumer and how access to personal data could help to provide better services.  In the mobile phone sector, for example, transparent pricing can not only help to stimulate the right kind of economic growth argues Thaler, but also that consumers could save considerable amounts of money by switching to the right plan. But to pick the best plan, you need to be able to estimate how much you use services like texting, social media, music streaming and sending photos.

James Beckland also discusses personal data and psychographics in this interesting Mashable article.  Buckley breaks personal data into three categories; social profile data, behavioural data and customer lifecycle data. We have discussed customer lifecycle data in our previous blog on marketing and we have also shared insight into our research on the analysis of gambling behavioural data too. Social profile data provides a rich new source of personal insight.  For example, organisations would very much like to know which affinity brands influence their best customers, which celebrities they follow, and the themes of the messages they regularly share.

Given that personal data is now i) exponentially increasing and ii) becoming increasingly valuable, what if your personal gambling data, data that describes in detail the games you play during each session you log on, all of your transaction details, details on your wins and losses, your social media interactions, chat room data, etc, could be easily downloadable and made available to share in a friendly format with other websites offering value-added services?  It is not inconceivable that one day players will be able to fully control who can see their personal data so that they can leverage it better, not only to get better deals, but also to make smarter decisions about their health and wealth. At Bet Buddy, one of the ways we are using data is to allow gamblers to make more informed decisions about their gambling.  For example take a look at Advisor, our player facing app, which provides rich, relevant, and interactive data insights for gamblers to help them make more informed decisions about their gambling.