Big data blocks gaming fraud
[Philip Lelyveld comment; So if big data allows the 'house' to identify players operating outside of their expected patterns, how big a step is it to develop an algorithm to increase the house's odds to just the point where the player's losses and hope are in optimal balance?]
Online game developers have vast amounts of rich, unstructured data at their fingertips that they could use to help achieve revenue stability. The data delivers an understanding of each player and what they are doing while in the game. That same data could be manipulated to identify and stop fraudulent game activities in real time.
Recently, we had the opportunity to test this premise with one of the world’s largest casual online gaming companies, which was plagued by revenue leakage due to cheating players. By using analytics to examine and model the game, we could determine common player navigational paths. We could then design mathematical algorithms that could place parameters around the average player and predict the average way he or she would progress in the game. This information determined the threshold range for what would be acceptable play; any players that fell outside of the threshold range would be flagged as being potentially fraudulent. The game developer could then choose to immediately freeze accounts for those advancing too quickly — thereby plugging the revenue hole.
Read more at http://venturebeat.com/2013/10/03/big-data-blocks-gaming-fraud/#BbG6PWUr4llMD03T.99
See the full story here: http://venturebeat.com/2013/10/03/big-data-blocks-gaming-fraud/