Client

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A US-based company offering an AI-augmented business risk monitoring solution for financial institutions in the BFSI sector.

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Problem

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The client needed to enhance their risk monitoring platform with financial intelligence that could scale across diverse banking institutions. While banks publish annual and quarterly reports containing critical information like asset quality, capital adequacy, provisioning, and liabilities, these reports are unstructured, lengthy, and inconsistent in format.

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To train models that could understand and interpret such financial disclosures, the client required a comprehensive, structured dataset covering both listed and unlisted banks in India. The challenge was to extract this data with accuracy, ensure consistency across institutions, and maintain auditability through source-linked records.

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Solution

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Globik AI built a complete data pipeline to source, extract, and validate financial information from 182+ Indian banks:

• End-to-End Data Collection: Annual and quarterly reports were sourced directly from official bank records and regulatory filings, ensuring coverage of both public and private sector banks.
• Deep Data Extraction: Key indicators such as Operating Profit, EBIT, Capital Adequacy Ratio (CRAR), Gross NPA, Net NPA, Return on Assets, Deposits, Liabilities, Assets, Liquidity Coverage Ratio (LCR), and Leverage Ratio were extracted and standardized.
• Structured and Transparent Output: Data was formatted into a machine-readable structure, with direct links to Annual Reports, LCR documents, and Leverage Ratio disclosures for full transparency.
• Expert Led Validation: Financial SMEs reviewed the dataset, validating every field against banking norms and ensuring consistency across institutions.

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Result

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The client received a unified and transparent dataset that transformed their platform capabilities:

• Risk monitoring models could interpret financial ratios and disclosures with improved accuracy
• Analysts gained faster insights through structured data instead of parsing hundreds of PDF reports
• Coverage of both listed and unlisted banks provided a more holistic view of sector-wide risks
• Regulatory compliance and audit confidence improved due to SME validation and source-linked transparency

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Why It Matters

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In the BFSI sector, risk monitoring platforms rely on reliable, comprehensive data. By building a dataset from 182+ banks, covering metrics from profitability to risk ratios, Globik AI enabled the client to train models that analyze banking risks with precision.

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This approach shortened analysis timelines, improved prediction accuracy, and delivered a foundation for long-term innovation in credit risk, compliance, and fraud detection.

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Share Worthy Snippets

• Structured dataset built from financial disclosures of 182+ Indian banks
• Expert-validated financial metrics powering AI risk monitoring solutions in BFSI
• Covers key ratios and indicators including CRAR, Gross NPA, Net NPA, ROA, Deposits, Liabilities, and LCR
• Transparency ensured with direct links to original bank reports and filings