Neutral NewsInside "Bribes.fyi": A Student-Built Platform Tracking Bribery Reports
Aryan Nishad, a Bachelor of Technology student at the Maharaja Agrasen Institute of Technology, launched "Bribes.fyi" on July 2, 2026.
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Aryan Nishad, a Bachelor of Technology student at the Maharaja Agrasen Institute of Technology, launched "Bribes.fyi" on July 2, 2026. The site allows citizens to report government bribery anonymously. By August 17, 2026, users submitted 616 reports from 251 cities. Police departments account for 337 of these entries, the highest count among all sectors. Approximately 38% of users reported refusing to pay bribes. The platform uses self-reported data and a simple verification checkbox. These limitations prevent the site from serving as a definitive measure of national corruption.
Context
Corruption reporting in India relied on government channels or investigative journalism. Digital crowdsourcing tools enable decentralized, user-driven data collection.
Supportive perspectives
The portal serves as a centralized hub for citizens to document bribery. Since its launch on July 2, 2026, the site has gathered 616 reports from 251 cities.
The system records data for specific sectors. Police departments submitted 337 reports. The Regional Transport Office (RTO) filed 88 entries.
A study found that some users declined to pay. Approximately 38% of them refused to pay the demanded bribe.
Users reported receiving government services after refusing to pay bribes. Citizens successfully challenged demands for illicit payments in these instances.
Critical perspectives
Users confirm their experience by selecting a checkbox on the platform. This process does not independently verify the reported information.
The data derives from a self-selected sample. These figures do not provide a scientific or definitive measure of corruption rates in India.
The platform lacks a formal investigative mechanism. It functions as a repository for reports rather than a tool for triggering government action or legal intervention.
Anonymous submissions carry a risk of false reports. The platform does not independently verify submissions to separate genuine from fabricated data.
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