Every year, banks across India publish hundreds of pages of financial reports. These documents contain vital details such as asset quality, capital adequacy, liabilities, and risk ratios. Yet the information is often unstructured and difficult to compare across institutions.

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A US-based risk monitoring platform partnered with Globik AI to solve this challenge. The goal was to build a structured dataset that could span over 182 Indian banks, including both listed and unlisted institutions.

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Globik AI designed an end-to-end pipeline to collect and process annual and quarterly reports directly from banks and regulators. Key indicators like operating profit, CRAR, gross and net NPAs, return on assets, deposits, and liquidity ratios were carefully extracted. To ensure transparency, every data point was linked back to its original source document. Financial experts then validated the entire dataset for accuracy and consistency.

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The results were immediate. Analysts gained faster insights without wading through countless PDFs, while the client’s models achieved higher precision in evaluating banking risks. Regulatory compliance and audit confidence also improved, backed by expert validation.

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This project highlights the value of transforming raw financial disclosures into structured intelligence. With the right data foundation, banks and financial institutions can improve risk management, enhance compliance, and accelerate innovation in credit scoring and fraud detection.

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