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Lottery Data Analytics Data Analysis/Investigations. October 2013. Data Analysis prior to 2009. Investigations with no data analysis to support claims Difficult to obtain data due to strict internal controls on access Data was available but not organized or in one central program or system
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Lottery Data AnalyticsData Analysis/Investigations October 2013
Data Analysis prior to 2009 • Investigations with no data analysis to support claims • Difficult to obtain data due to strict internal controls on access • Data was available but not organized or in one central program or system • 30 day limit on availability of lottery transactions (purchases/validations) • Customers were responsible to know their prize and ticket in hand held a lot of weight in prize payment
Organizational Changes • Fifth Estate program focused on OLG • Ombudsman’s Report • Media and public interest in suspicious prize claims by insiders • OLG changed to increase: • Integrity • Risk Management • Customer Focus • Controls • Data Analysis
Data Analysis – A New Team • Two teams were created to help modernize our systems to support data analysis • Technology: developing the tools and programs to assist in analysis • Analysis: extract the data and analyze the information to support claims and identify retailer theft, fraud or dishonestly
Current Capabilities • Selection Searches • Retailer comparison reports • Lottery transactions (purchase/validations) back to March 1999 • Prize claims processed through the prize centre (customer’s previous wins)
Developing Customer Profiles • Following these tickets we can develop unique play patterns such as: • unique spend could be the dollar value of total purchases, • whether or not the customer plays selection or quick pick, • whether or not the customer plays ENCORE and the number of ENCORE played • what lottery products they play/mix of lottery products they play • the unique locations that the customer purchases/validates their tickets, • the cities that the customer purchases/validates ticket and • the days of the week/time of the day that they are purchasing/validating their tickets
Profiling Selections • One of the first charges laid by the OPP on lottery theft was a claim from a retailer. • The winning ticket was a selection (customer picked their own numbers). • OLG reviewed lottery transactions following the selection back from 2001 to 2008 • Develop a profile that included: • Location/city that the customer played at • Day and time of purchases/validations • Identify slight change in the numbers selected • Changes to customer spend • This was OLG’s first player profile
Chung Case • Profiling was done on both the customer and on the retailer behaviour • What we learned about the retailer: • Anomalous Retail Behaviour • Validated these tickets together on certain days of the week • What we learned about the customer • Played on certain days and time • Played between two cities • Specific spend on specific product • This told us the customer lived in one city and worked in another • Potential to be a group play
Profiling Today’s Winners • Ability to profile the customer and develop questions where we already know the answers • For one of OLG’s latest winners we were able to build a robust profile of the customer including • where we believed he lived • where and when he purchased lottery tickets • how he validated tickets • Lottery products played and spend • how long he has been playing the lottery • where he vacationed this summer • OLG was also able to identify that the winning ticket was not likely a group based on the numbers selected.
