SIH26102Software
Development of an AI-powered system to detect anomalies, fraud, and inefficiencies in MPLAD Scheme implementation regd.
MoSPI
Official Description
• 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.
Official Hackathon Facts
Theme / DomainMiscellaneous
Track TrackSoftware
Submission Deadline20 September 2026
Ideas Registered0/500
Source DatasetExternal Resource ↗
✨ SIH Fit Analysis
Estimated DifficultyIntermediate
Social Impact Score (3/5)
🌍 High Social Impact
Primary Tech AreaAI-based Prediction / Recommendation
Technology Stack Tags
AI/MLPredictive AnalyticsAnomaly DetectionFraud DetectionWeb Development
Suggested Skills
PythonTime-series modellingReact / Node.js
✦ Why This Problem is Interesting
Combines Predictive Analytics with the problem domain, creating a technically focused solution opportunity.
* Note: SIH Fit Analysis contains derived ratings and classification schemas generated to aid team selection; these are not official ratings from the Smart India Hackathon organizers.
