UPI based mobile payments have risen to an astounding 16.61 million in Aug 2017. This big number also indicates that mobile payments in India are now part of big data. Big data has been around since the conception of Information Technology; it involves the collection and processing of a large amount of data for legal use. Big data technology has evolved through the ages and today is primarily accessed via cloud-based computing technology.

In India, the government took a major step in prioritizing the need for big data, and the usage of big data was evident during the General Elections 2014 when the BJP accessed large amounts of researched data on the public’s reaction to their many political reforms. Now that mobile payments are becoming a rising trend in the country, the implementation of big data analytics on mobile payments is essential, as it could help standardize the payment method. Here are a couple of ways big data can revolutionize mobile payments.

Enhances the consumer’s experience

At present, the shopping experience is pretty straightforward; consumers will access their phones to purchase their needs through an e-shopping app. With big data analytics, the shopping experience will get enhanced to become more personal. Consumers will be alerted on the best products in the market based on their likes interests and location. Consumers also have the advantage of customising their shopping preferences directly on apps, so when big data analytics picks up this information, consumers will be treated to a more refined shopping experience that is non-intrusive and concise.

Allows retailers to get better consumer insights

No matter the type of payment or the variety of products, the retail industry is one of the most competitive in the marketplace. The competition will only get stiffer with big data analytics in play. Retailers who adapt to tech-friendly shopping methods like POS Systems and QR Enabled Payments faster will gain an advantage over their competitors, as big data analytics will enable them to access unique information regarding a consumer’s shopping interests. With such information, retailers can avail special discounts and other value-added services to consumers, effectively boosting their sales and improving consumer relations.

Seamless integration of multiple payment methods

Consumers aren’t just spoilt for choice over products; they even have multiple ways of paying for their necessities today. Big data analytics lets retailers figure out each consumer’s preferred way of paying, and with this information, retailers can provide an even moreniche shopping experience. Consumers are also getting very impatient regarding the time it takes to get their purchase needs sorted out. Big data analytics is paving the way for the seamless integration of payment options, with many shopping apps already letting consumers save their payment preferences, hence shortening down the purchase time.

Eliminates payment errors/risks

Cash payments come with numerous drawbacks, one of the biggest being that retailers find it hard to maintain accounts with hard currency, especially in large volumes. Digital payments have solved that problem, but are still susceptible to occasional hicks in transactions if there is a poor internet connection.  Big data analytics has a unique architecture that collects and stores data in clusters. These clusters keep the data from being disorganised or mishandled, so if payment information is typed in by a consumer, it will be stored in a cluster that is exclusive to thatconsumer’s purchase history and behaviour.

Pushes the need for extreme security measures

Big data in India is being tested through the implementation of the Aadhaar Card system and its supporting Aadhaar Pay app. There were many initial concerns over the privacy and security of the new system, but the government has assured that strict security measures like the Central Monitoring System (already active in Delhi), which will automate security measures against illegal activity. The newly introduced Tokenisation system is poised to replace sensitive data that is used to confirm payment procedures, with unique tokens.

The next time you find yourself faced with multiple queries and access requests from apps, you’ll know that it is all for the greater good that comes along with big data analytics. Mobile payment systems are continuously evolving, and the need for big data analytics will increase tenfold when social media apps start allowing payments.


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