• Background The Members of Parliament Local Area Development Scheme (MPLADS) is a Central Sector Scheme under which Hon'ble Members of Parliament recommend developmental works for creation of durable community assets and provision of basic civic amenities. The Scheme involves large-scale fund utilization and execution of thousands of works across the country through multiple implementing agencies and administrative authorities. Given the volume and complexity of financial and project-related data generated under the Scheme, there is a need for an AI-powered solution that can leverage machine learning and advanced analytics to detect trends and anomalies in expenditure patterns, fund utilization, cost estimates, and work execution, thereby enabling early identification of potential fraud, inefficiencies, and non-compliance while enhancing transparency, accountability, and effective monitoring of MPLADS works. • Description Develop an AI-powered monitoring and analytics platform for MPLADS that leverages Machine Learning (ML), Artificial Intelligence (AI), and advanced data analytics to identify trend, anomalies, irregularities, and potential fraud in fund utilization and project execution. The solution should analyze data relating to sanctions,expenditures, cost estimates, work progress, payments, and asset creation to detect unusual patterns, cost overruns, duplicate works, delayed projects, and deviations from established norms. The system should generate risk-based alerts, predictive insights, and decision-support dashboards for Members of Parliament, State Nodal Authorities, District Authorities, and the Ministry. The platform should also facilitate automated compliance monitoring, trend analysis, and early warning mechanisms to improve transparency, accountability, and efficiency in the implementation of MPLADS works across the country. • Expected Solution The proposed solution should be an AI-powered platform that helps monitor MPLADS works and fund utilization in a smarter and more efficient manner. By analyzing data related to project approvals, expenditures, payments, work progress, and completion status, the system should be able to identify unusual patterns, delays, cost overruns, duplicate works, and potential cases of misuse of funds. It should automatically generate alerts and highlight high-risk cases that require attention from the concerned authorities. The platform should provide easy-to-understand dashboards and insights to Members of Parliament, State Nodal Authorities, District Authorities, and the Ministry, enabling them to make informed decisions and take timely corrective action. By leveraging artificial intelligence and data analytics, the solution should enhance transparency, strengthen accountability, reduce manual monitoring efforts, and support more effective implementation of MPLADS works across the country.
Development of an AI-powered system to detect anomalies, fraud, and inefficiencies in MPLAD Scheme implementation regd.
MoSPI
- Ideas submitted
- 294 / 500
- Deadline
- 30 September 2026
- Category
- Software
- Theme
- Smart Automation
Looks like it needs
How contested this one is
as of 28 SeptThat puts it 33rd of the 240 statements that have any ideas at all, out of 240 on the board. It is moving, so the field here is already forming.
See what the whole field is picking →Counted from the official portal twice a day. The portal itself only shows today.
What a jury will ask about this
01“Who actually faces this problem today?”
What works: Naming one real person and what they do instead right now. Reading the statement back is not an answer, they already read it.
02“This already exists. Why yours?”
What works: That existing tools are consumer products. Yours is built for the ministry, works offline, in the local language, on official data.
03“Then why has nobody solved it yet?”
What works: The real blocker. No connectivity, no incentive, nobody owns the data. You only know this if you read the ministry's own reports.
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