Equity Research
A leading investment management group relied on manual equity research workflows that slowed decision-making and limited scalability. Broker reports were lengthy, inconsistent, and packed with dense financial data. With Maisa Digital Workers, the firm automated the extraction and structuring of insights from these reports, turning unstructured content into actionable intelligence in minutes and enabling analysts to focus on high-impact investment strategy.
Industry
Banking & Financial Services
Department
Banking & Financial Services, Wealth and Investment Management
The Challenge
Equity research plays a central role in investment decision-making, but it depends on time-intensive manual analysis of broker reports. Each document contains a mix of charts, tables, and complex commentary that analysts must read, interpret, and summarize before producing insights for portfolio managers and clients.
The research team faced a growing backlog of unstructured documents and lacked standardization across sources. Each report took about thirty minutes and nearly twenty manual steps to process, from data extraction to summary preparation. As the volume of broker coverage expanded, analysts struggled to maintain quality, consistency, and timeliness.
Traditional automation solutions could not handle the variety of file formats or understand the financial and qualitative nuances of the reports. This limited the firm’s ability to scale coverage, accelerate research cycles, and respond quickly to market shifts.
The Solution
Using Maisa Studio, the firm’s Wealth and Investment Management team created a Digital Worker that processes broker research reports end to end. Built without coding and guided by natural language instructions, the worker extracts, interprets, and structures insights with precision and consistency.
Data Extraction and Structuring
The Digital Worker reads and parses text, tables, and charts from PDF reports regardless of layout or formatting. It identifies relevant sections and converts them into standardized, machine-readable fields ready for analysis.
Insight Summarization
Summarizes target prices, recommendations, earnings expectations, and qualitative commentary into concise, structured insights, aligned with the firm’s reporting formats and KPIs.
Automated Output Generation
Creates ready-to-use outputs such as Excel templates and narrative summaries, enabling analysts to review and share insights instantly across teams and systems.
Scalability and Adaptability
Scales seamlessly across brokers and research teams with minimal setup, allowing rapid expansion of coverage across asset classes and sectors without additional engineering effort.
By integrating document intelligence with domain expertise, Maisa Digital Workers turned a manual research workflow into a scalable, automated intelligence system for investment analysis.
The Results
Faster Coverage
Research reports that once required extensive manual review are now processed in less than five minutes.
Analyst Enablement
Structured insights accelerate decision-making and allow analysts to focus on strategic analysis rather than administrative tasks.
Foundation for Scale
The automated process enables consistent and rapid processing of large volumes of broker research, creating a foundation for global research scalability.
Path to Advanced Intelligence
Establishes a roadmap for future AI-driven research synthesis, enabling cross-broker comparisons and multi-document insights at scale.
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