In addition to enabling real-time identification of procurement concentration and cartel risk indicators, CAG, the country’s top auditing body, is developing a large-scale language modeling platform to significantly improve the quality, speed, and depth of analysis of public audits.
Auditor General K. Sanjay Murthy said on Wednesday that auditors will leverage this integrated data and use anomaly detection tools, predictive risk scoring models and network analytics to map procurement across India.
“Our modernized audit system will more quickly and efficiently identify patterns of repeated bid rotation, suspicious clustering of vendors, unusual pricing similarities, concentration of bids, and limited competition across bids,” he said at an event in the capital.
Murthy said the vision going forward is to be able to identify procurement concentration and cartel risk indicators in near real-time. “Future audit analysis could ultimately generate a dynamic competitive risk heatmap across sectors, regions, and contractor ecosystems.”
Speaking as the guest of honor at the 17th Annual General Meeting of the Competition Commission of India (CCI), he said the CAG’s audits, which focus on procurement across key industries, have moved from reporting isolated isolated irregularities to identifying larger systemic patterns.
CAG is deploying artificial intelligence (AI) and machine learning (ML) tools to analyze the entire data.
Murthy said the various offices of the Comptroller and Auditor General of India produce around 20,000 to 25,000 audit reports each year containing hundreds of thousands of audit findings related to government spending, infrastructure projects, taxation, procurement, etc.
He said CAG LLM is being developed as a sovereign artificial intelligence platform for public sector auditing and organizational knowledge management.
He said: “These LLM platforms are expected to significantly improve the quality, speed and depth of analysis in public audits by assisting officials in identifying risk areas, designing audit plans, detecting system vulnerabilities, and enabling faster sharing of organizational knowledge and best practices across various stakeholders.”
Additionally, with improved capabilities, CAG aims to build deeper analytical capabilities to assess GST systems, FASTag and logistics datasets, mine dispatch systems, power exchanges, transport networks, and public procurement repositories.
(This story has not been edited by Devdiscourse staff and is auto-generated from a syndicated feed.)
