In the high-stakes world of equity research, time is money — but so is accuracy. A leading financial advisory and compliance consulting firm, serving over 150 global and Indian financial institutions, was spending an enormous amount of analyst time manually combing through annual reports and regulatory filings.
Our team partnered with them to design an AI-powered equity research copilot that could read, understand, and extract valuable insights from these complex documents — with full data privacy.
Executive summary:
A leading financial advisory and compliance consulting firm serving over 150 global and Indian financial institutions faced a major challenge: their analysts spent 4–5 hours manually reviewing each annual report and regulatory filing, often exceeding 300 pages of complex, unstructured financial data.
The process was repetitive, required deep domain expertise, and slowed research output.
We implemented a custom AI-powered equity research copilot using Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG), hybrid OCR + vision-based parsing, and on-premise execution for complete data privacy.
The results:
- 80% reduction in time per document (from 4–5 hours to under 1 hour)
- 4x increase in companies covered per quarter
- 97%+ accuracy in data extraction across diverse formats
- Zero compliance breaches
This transformation allowed the client to scale their research capacity, maintain regulatory compliance, and deliver faster, more accurate insights to their institutional clients.
Client’s challenge:
1. Document complexity
The firm’s analysts handled hundreds of reports every quarter — each between 100 and 300+ pages, filled with legal jargon, multi-level tables, and financial disclosures.
2. Manual, Time-Consuming Process
The existing process involved:
- Manually reading large sections of text
- Using Ctrl+F to search for known keywords
- Copy-pasting relevant sections into internal templates
This required deep domain expertise and took 4–5 hours per document.
3. Unstructured formats
Annual reports and regulatory filings varied drastically in structure, making it nearly impossible to use traditional parsing tools without heavy manual intervention.
4. Repetitive workflow
The same process was repeated for every company, every quarter, eating into analysts’ time for higher-value research.
AI opportunity assessment:
When we conducted a workflow analysis, three clear automation opportunities emerged:
- Information extraction from unstructured text: Extract MD&A, risk factors, and financial statements without reading every page.
- Multi-format parsing: Handle scanned PDFs, tables, and charts as easily as text-based filings.
- Consistent, repeatable analysis: Standardize parsing so every document followed the same structured output format.
Our AI-Driven solution:
1. Custom Equity Research copilot
We developed a domain-tuned Large Language Model (LLM) powered by Retrieval-Augmented Generation (RAG):
- Ingests annual reports, MD&As, earnings transcripts, and filings.
- Answers analyst queries with precise, citation-backed responses for full auditability.
- Understands finance-specific terminology to ensure accuracy.
2. Hybrid document parsing
- Combined Optical Character Recognition (OCR) with layout-aware vision models to:
- Extract data from tables, footnotes, and multi-column layouts
- Detect and parse scanned content as effectively as digital PDFs
- Maintain original data relationships for better context
3. On-Premise execution for privacy
- All AI processing was deployed inside the client’s infrastructure.
- No public APIs or cloud dependencies — ensuring strict compliance with financial regulations like SEBI, RBI guidelines, and client-specific NDAs.
Results & Measurable impact:
| Metric | Before AI | After AI | Improvement |
|---|---|---|---|
| Time per document | 4–5 hrs | <1 hr | 80% faster |
| Analyst coverage per quarter | ~50 docs | 200+ docs | 4x increase |
| Data extraction accuracy | ~85% | >97% | +12% gain |
| Compliance breaches | 0 | 0 | Maintained |
Key outcomes:
- Analysts could cover more companies and sectors per quarter without increasing headcount.
- Higher accuracy meant fewer missed risk factors and more confidence in investment recommendations.
- Research reports reached decision-makers faster, improving client satisfaction.
Why This Matters for Equity Research Firms:
In a sector where regulatory compliance, accuracy, and speed all matter equally, the ability to:
- Parse unstructured, multi-format financial documents
- Answer complex, domain-specific queries instantly
- Maintain full control of sensitive data
This AI solution not only solved today’s bottlenecks but future-proofed the client’s research workflows for emerging regulatory and data privacy demands.
Ready to transform your business with AI?
At InteligenAI, we specialize in building practical, scalable, and production-ready AI solutions across all industries for businesses of all scales. To explore custom AI solutions, contact us or book a free consultation with our founder and AI strategist.