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Indian govt issues notice to Ola and Uber over alleged fare disparity on iPhone, Android devices

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Sumit Vishwakarma
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govt issues notice to Ola and Uber

The Central Consumer Protection Authority has issued notices to ride-hailing giants Ola and Uber after receiving complaints of alleged unfair trade practices. 

According to Consumer Affairs Minister Pralhad Joshi, the companies are under scrutiny for charging different fares based on whether customers use an Android phone or an iPhone.

He shared the news on X and described such differential pricing as a “prima facie unfair trade practice” and a breach of consumer rights.

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Complaints and early signs of disparity

The issue came to light after some commuters reported that identical rides showed higher fares on iPhones compared to Android devices. A Times of India report highlighted this disparity in Chennai, where fares searched at the same time and for the same routes often appeared higher on iPhones.

Although there has been no formal proof that these differences were intentional, the matter raised enough concern for the Department of Consumer Affairs to request a thorough explanation from both companies.

In some instances shared on social media, customers posted screenshots showing that the same Uber Auto ride cost one amount on an Android phone and a higher amount on an iPhone.

One user said he had started asking his daughter to book rides on her phone to avoid paying more. This post led other users to come forward with similar stories, suggesting that differential pricing might be more common than initially thought.

Official response and investigation

Minister Joshi said that the Department of Consumer Affairs, through the CCPA, has asked Ola and Uber to respond to these allegations. 

The notice follows the minister’s earlier promise of “zero tolerance for consumer exploitation,” and he called for transparency in how ride-hailing apps set their fares.

For now, Ola and Uber have not issued a public response to the notice. Industry observers, however, suggest that advanced algorithms powered by machine learning may be behind these variations, taking into account user behaviour and possibly device type. Critics argue that such tactics, if proven to be deliberate, would undermine consumer trust.

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