Casinos and Gaming

AI Use Cases in Gaming

• Future Player Behavior

  Understanding when a patron is likely to play next, how much they will play, and if they’ll use their offers allows casinos to better focus their marketing efforts. By using an end-to-end enterprise AI platform, gaming companies can make targeted marketing decisions — offering the right deal at the right time to the right audience in order to drive maximum spend at the establishment.

• Lifetime Value

  Go beyond simply understanding the historical value of a player’s behavior and build machine learning AI models that capture what their behavior might be in the future. Using automated machine learning, companies can build better marketing programs, identifying players who are deemed more valuable and develop them into loyal customers.

• Player Churn

  It costs significantly less to upsell an existing customer than to bring in a new customer. The right machine learning models can help do exactly that — identifying customers unlikely to play at the casino again, as well as why they might drop off, and providing the tools to retain them. The models built with enterprise AI can determine what offers are most likely to bring customers back, when to make those offers, and how to accurately target them.

• Anti-Money Laundering

  Many rule-based systems for identifying money laundering generate too many false positives, wasting time by investigating legitimate behavior. Predictive models can help minimize these false positives and focus resources on actual money laundering cases that need immediate attention, both internal and external.

• Floor Optimization

  Using historical data, AI can help build models to understand why certain games perform the way they do, based on factors such as type or location. Use that valuable information to decide where to place games on the casino floor for optimal return.

• Anti-Cheating

  AI can help gaming companies build models that detect cheating by quickly and automatically identifying suspicious behavior by either players or employees. This enables security teams to flag the behavior for further investigation.

• Demand Forecasting

  Based on forecasts of how many players and guests will be at the property at a given time, predictive models built with enterprise AI can help determine when to schedule staff working hours and how to make the appropriate purchasing decisions for food, beverage, and merchandise.