New Delhi: In a bid to create AI-powered solutions that help in monitoring financial reporting quality and speed up internal tasks, the government has announced the ‘IndiaAI Financial Reporting Compliance Challenge’.
The National Financial Reporting Authority (NFRA), in partnership with IndiaAI, has launched the challenge to solicit AI-driven solutions.
Participants will compete for a total prize pool of Rs 1.5 crore, with up to 10 teams receiving Rs 5 lakh each during a virtual refinement stage, and one winner potentially securing a two-year contract with NFRA worth up to Rs 1 crore for national-scale deployment.
The initiative invites Indian companies and DPIIT-recognised startups to develop an advanced engine capable of extracting data from multi-format documents and validating them against frameworks.
“The challenge seeks to produce explainable compliance validation reports, automated analytics for risk indicators, and an AI-enabled insight bot to support the NFRA’s mission of safeguarding public trust and investor interests. Applications are currently open and will close on February 22, 2026,” according to an official statement.
Last week, Prime Minister Narendra Modi exhorted India’s AI startups to ensure that their models are ethical, unbiased, transparent, and based on data privacy principles.
The Prime Minister urged them to work towards global leadership from India as the country can promote affordable and inclusive AI, as well as frugal innovation globally.
He also suggested that Indian AI models should be distinct and should promote local and indigenous content and regional languages.
PM Modi highlighted the importance of artificial intelligence in bringing about transformation in society. He noted that India will host the India AI Impact Summit 2026 next month, through which the country will play a major role in the technology sector.
The Prime Minister emphasised that startups and AI entrepreneurs are the co-architects of India’s future and said that the country has immense capacity for both innovation and large-scale implementation.
(IANS)
