GamStop and Data Science: How to Benefit from It?


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Data extraction and the use of that data to forecast an unforeseen result of a scenario is a major aspect of progress in today’s digital environment. This is something that almost everyone today is aware of. The gaming industry’s tremendous growth is also an illustration of how data may be used to help a certain industry thrive. The United Kingdom Gambling Commission has urged NonStopCasino sites that aren’t on GamStop to make progress in key digital spaces by October 2019 in order to raise their player safety standards. 

They were in charge of things like customer engagement, micro-advertising, and other similar aspects. While determining certain standards is rather simple, recognizing certain elements requires entirely academic methodologies such as the application of fundamental data science. Considering the newest services provided by these online casino providers, maintaining a database is what keeps the actions flowing. For instance, in order to prohibit casino sites, data collecting is required; otherwise, the entire system will crash. The same theory can be used to meet the requirements for operator protection. This data can be maintained by UKGC for different legal formalities, which is also important for resolving technical issues.

The type of data in use by GamStop

To begin with, the type of data collected includes basic customer data such as name, email address, phone number, date of birth, and, in certain cases, residential and office address. However, GamStop’s main goal is to collect more data over time in order to support the company in the long run by improving its services. Here customer service representatives play an important role since they extract miscellaneous information from the context of numerous reasons. 

The call recordings are used to back up the information gathered. Larger firms in the same industry may borrow a large portion of it from the operators. Verifying the collected information to ensure accuracy is one of the most crucial activities for these companies. Inaccurate big data may have an impact on the quality of services offered. The TransUnion database can be used for verification, or the data acquired can simply be maintained in a database. The end goal is to collect authentic data that can be preserved for future usage for a long time. 

The outcome of this data collection

Two major findings from the data collection can be noted as:

  1. People who want to overcome their gambling addiction can directly join the GamStop self-exclusion scheme as a voluntary step towards self-reflection and correction.
  2. The cooling-off period of 24 hours is the first step in detecting any signs of gambling addiction if present in a seasoned gambler.

Detection of problematic gambling

Certain industry-level identifiers can be put to work to categorize people into four different sections in terms of addictive tendencies. Such classifiers are: 

  • The number of sessions played in a certain period of time is referred to as frequency;
  • Variability, which is concerned with a shift in a player’s gambling habit;
  • The time spent and bets placed in a minute of a whole session of a played game is called intensity.
  • Trajectory refers to the change in pattern over time as a result of the application of three key indicators mentioned earlier.

Using these harm signals can often aid in the development of player protection. Another important element is the perseverance of players who are constantly looking for ways to get over the GamStop prohibition. In order to forecast the demographics’ and individual players’ behavioral patterns, a multitude of machine learning models is used. These facts aid in the development and often modeling of the algorithm.

The data retrieved is solely meant for the protection of gamers. Although there are a few blind spots that should be addressed, they can be divided into two categories. This has to do with admitting to having compulsive gambling habits. The fact that not every player in need of self-exclusion will choose self-exclusion and that not every player who chooses self-exclusion has gambling addiction difficulties. There may be instances where a person is experiencing significant losses in the financial industry yet continues to gamble away their money.


The amount of data stored by GamStop is not always politically ideal. Still, given how effective it is in detecting problem gambling and the potential of it to recover people from gambling problems, it is almost acceptable considering the bright side. GamStop API can now harvest data from operators in the UK and preserve it for up to 14 years which is, although questionable, for similar reasons it gets a pass without the intentions of getting questioned. 

Photo credit: The feature image has been done by Amnaj.

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