New Delhi: The Indian Railway’ catering and ticketing arm, IRCTC has withdrawn a controversial tender for hiring a consultant to monetise its passenger and freight customer data following concerns over privacy, reported news agency PTI quoting officials on Friday. IRCTC informed the Parliamentary Standing Committee on Information Technology chaired by Congress leader Shashi Tharoor on Friday that it was no longer pursuing the tender.Also Read – IRCTC Latest Update: Railways to Begin Superfast Trains Between Delhi And Indore. Check Full Schedule Here
The parliamentary panel had summoned officials of the Indian Railway Catering and Tourism Corporation (IRCTC) following a PTI report on the tender for the appointment of a consultant for digital data monetisation. IRCTC MD and Chairperson Rajni Hasija deposed before the panel along with other officials. Also Read – IRCTC: Order Food On Train in Zoop Now Through WhatsApp. Step-by-step Guide Here
“IRCTC has withdrawn the tender in light of the non-approval of the Data Protection Bill,” an IRCTC official informed the panel. The decision to withdraw the tender was taken at the IRCTC annual general meeting on Friday, ahead of the panel hearing. Also Read – Ganesh Chaturthi 2022: Indian Railways To Run Ganpati Special Trains Between THESE Cities; Check Full List Here
What did the tender advertise?
According to the tender document, the data to be studied will include information captured by the national transporter’s various public-facing applications such as name, age, mobile number, gender, address, e-mail ID, class of journey, payment mode, login or password” and other details. The IRCTC has more than 10 crore users, of which 7.5 crore are active ones.
The tender document, titled ‘The Scope of Work for Project A: For study of Monetization of Digital Data of Indian Railways (IR)’, stated the consultant would also be provided access to the digital data systems which generate behavioural data such as flow of passengers, class of journey, frequency of journey, travel time, booking time, age group and gender, payment mode, number of destinations and booking modes.
(With PTI inputs)
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