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FingerMotion Inc. (FNGR) Leveraging Raw Mobile Data to Offer Big Data Insights
May 4, 2021

FingerMotion Inc. (FNGR) Leveraging Raw Mobile Data to Offer Big Data Insights

  • FingerMotion has forged strong relationships with the three largest telecommunication companies in China
  • The relationships have given FNGR access to subscriber data, allowing it to test its proprietary data analytics algorithms in real-time
  • The algorithms, created by FingerMotion’s Big Data Insights Division, leverage raw mobile data to create a user persona

A technological company, FingerMotion (OTCQX: FNGR) has evolved over the years. What began as a mobile gaming company, launched in 2016, morphed into a mobile payment and recharge service provider in 2018, offering these services to China Unicom’s (NYSE: CHU) customers. That same year, FNGR was awarded a contract to become CHU’s big data analysis partner, with success from this agreement leading to a similar arrangement with China Mobile the following year. In 2019, the company began offering mobile payment and recharge services to the users of both China Mobile and China Telecom (NYSE: CHA).

“We began by forging relationships with the three telecoms in China, China Telecom, China Mobile and China Unicom. By building up our relationships and providing consistent and dependable service, they have, in turn, given us unprecedented access to their respective user bases. This allows us to target telecom users with innovative products in an unobtrusive manner,” FingerMotion CEO Martin Shen said in a presentation during the Emerging Growth Conference (

The relationships with the three telecommunication companies, whose combined subscriber base as of 2020 stood at over 1.5 billion users (, helped FingerMotion venture into the big data insights business.

Shen, who described the company’s Big Data Insights division as the most exciting, noted in a separate webinar address ( that this division comprises a team of data scientists and actuaries who have developed proprietary algorithms to predict human behavior. FNGR then leverages its relationship with the telecommunication juggernauts to run these algorithms in real-time and off a secure database.

“We’re well-positioned to capitalize on the continually growing power of mobile data, transforming telecommunication signals into data blocks and integrating them with a host of external data and auxiliary information for mining and analyzing behavioral insights,” Shen added.

According to Shen, the company aims to create an integrated data ecosystem through technology and innovation. To do this, it intends to start with offering enhanced efficiency and user experience in mobile communications and subsequently extend the scope to deeper consumer behavior analytics, anchored on a comprehensive set of high quality and relevant mobile user data. This approach will enable the company to meet the needs of its customers through products and partnerships.

FingerMotion, which intends to ultimately offer products for the insurance, healthcare and finance sectors, is initially focusing on insuratech. This focus was evident in January when the company announced it has partnered with Pacific Life Re-insurance, in effect becoming its data provider. Notably, the partnership will extend beyond simply providing data as FNGR will also offer behavioral analytics, which Shen described as “brief insights into human nature itself.”

To generate the data insights, FingerMotion’s algorithm will rely on raw mobile data, including rudimentary information such as age, gender and place of residence. The algorithm will overlay this basic tier with a person’s geospatial information, such as places they have visited, to learn about the person and what they do throughout the day. Finally, it will utilize the individual’s internet usage, as well as call and SMS data.

However, it’s important to remember in all of this that the personal information is scrubbed, and only demographic information is used to create the data packets that personify the mobile data. By superimposing the four tiers, the algorithm can create anonymous data packets that personify the mobile data, describing the phone usage with parameters such as their occupation, number of hours they work, fitness level and more. FingerMotion is clearly leveraging raw mobile data to offer a big data asset that can significantly help companies.

For more information, visit the company’s website at

NOTE TO INVESTORS: The latest news and updates relating to FNGR are available in the company’s newsroom at

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