Identify customers most likely to exhibit harmful gambling behavior.

Overview

The gambling industry, including online and remote gambling, is experiencing rapid growth. With advances in digital technologies, there is an increasing volume of customer data that operators can leverage to enhance customer experiences and ensure responsible gaming. However, the same technological evolution has also brought the challenge of identifying and mitigating harmful gambling behaviors, which can lead to severe consequences for individuals and significant regulatory repercussions for operators.

Problem Statement

Gambling regulators mandate that remote gambling operators actively utilize the wealth of customer data at their disposal to identify and mitigate harmful gambling behavior. Failure to detect and act upon such behaviors early on can not only lead to severe financial harm for customers but also result in hefty penalties and compliance actions against operators.

Solution Overview

Leveraging sophisticated machine learning models can greatly enhance the ability of gambling operators to identify and mitigate harmful gambling behavior. By utilizing AI-driven models, operators can analyze vast amounts of customer data in near real-time, ensuring that signals of harmful gambling behavior are identified early and accurately. These models can detect complex patterns and correlations that may not be evident through manual assessment, enabling a proactive approach to customer welfare management. The AI models can process thousands of customer events and transactions to pinpoint risky behaviors. This allows the Customer Interaction team to prioritize their efforts on the most at-risk customers. Intervention strategies can then be tailored accordingly, such as scheduling a phone call, restricting bet amounts, or freezing accounts to prevent further harm.