SIH26102SoftwareMoSPI

Development of an AI-powered system to detect anomalies, fraud, and inefficiencies in MPLAD Scheme implementation regd.

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

The Ask

Real Struggle

Given the volume and complexity of financial and project-related data generated

Expected Solution

Develop an AI-powered monitoring and analytics system for MPLADS that leverages Machine Learning (ML), Artificial Intelligence (AI), and advanced data analytics to detect trend, anomalies, irregularities, and potential fraud in fund utilization and project execution. The expected system must 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 system should also facilitate automated compliance monitoring, trend analysis, and ea

By analyzing data related to project approvals, expenditures, payments, work progress, and completion status, the system should be able to detect unusual patterns, delays, cost overruns,...
It should automatically generate alerts and highlight high-risk cases that require attention from the concerned authorities
By leveraging artificial intelligence and data analytics, the expected system must enhance transparency, strengthen accountability, reduce manual monitoring efforts, and support more effective...

Development of an AI-powered system to detect anomalies, fraud, and inefficiencies in MPLAD Scheme implementation regd.

Background

The Ask

Real Struggle

Given the volume and complexity of financial and project-related data generated

Expected Solution

By analyzing data related to project approvals, expenditures, payments, work progress, and completion status, the system should be able to detect unusual patterns, delays, cost overruns,...
It should automatically generate alerts and highlight high-risk cases that require attention from the concerned authorities
By leveraging artificial intelligence and data analytics, the expected system must enhance transparency, strengthen accountability, reduce manual monitoring efforts, and support more effective...