How Big Data Analytics and Gamers Could Solve Fraud and Security

How Big Data Analytics and Gamers Could Solve Fraud and Security

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Why gamification makes sense with big data analytics

Gamification has drawn much inspiration from games and gamers in tackling real world problems. Just to name a few, video game titles such as World of Warcraft and Simcity are revolutionizing lesson plans, Portal 2 was used as a talent recruitment tool and a puzzle game helped to unlock parts of the AIDS protein structure. These developments have allowed significant progress in their respective fields. Yet, how do we tackle the burning issues of security and fraud in an enterprise scenario? While it may seem daunting at first glance, we could once again draw key lessons by literally observing gamers and combining big data analytics.

First and foremost, regardless of whether it is a virtual game or a real-world “game”, there will be a segment of users that will actively find the path of least resistance by figuring out ways to game the system for their own benefit. If left unchecked, the results of their actions would often negatively impact other users.

Average users may be discouraged to continue their efforts while some may in turn join on the cheating bandwagon. To combat this, an admin’s standard procedure would be to individually track a suspicious user’s digital footprint on a micro scale but it is often tedious, time consuming and expensive. At this rate, all seems to be a lose-lose situation for both users and enterprises.

However, all is not lost as we take a few steps back. When a system is constructed, whether it is an online game or within an enterprising organization, raw data is constantly generated by its users’ actions and stored onto servers. When these vast quantity of unstructured data are compiled and analyzed through analytical programs, amazing things begin to happen.

As designers are provided with quantitative values of how users would perform activities, algorithms could be drawn up to define averages, as to how an average player would progress “normally” within the system. With that, a threshold range could be established which predicts what is considered normal play.

The algorithms could detect offending users such as those who create multiple accounts in order to artificially boost their main standings could be detected by examining the relationship patterns the accounts share as well as the win/loss ratio acquired. Besides that, analytics could reveal “whales”, or users who exhibits excessive spending behaviors in advancing their progress within a system.

This phenomena may actually turn out to be users who are utilizing stolen credit cards to further their virtual goals. Based on these possibilities, erratic behavior which would appear as outliers beyond the acceptable range, could be flagged for suspicious behavior and proper measure to be taken thereafter.

Big data analytics, obtained through users feedback is fast becoming one of the primary tools for designers and developers to create engaging content while conducting constant reiteration to improve overall user experience. In essence, researchers and organizations especially those in the enterprise sector have begun to appreciate the importance of understanding a gamer’s motivation and psyche based on their actions revealed through gameplay. Many organizations could manage to learn a thing or two from games and gamers well into the far future.

via Harvard Business Review | Image by infocux Technologies

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