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Finster
Your investment insights, faster.

What is Finster?

Finster is an AI-driven tool that supports investment analysts in making well-informed, meticulously researched decisions, at an unprecedented pace. Developed by a team with experience across finance, AI and tech from Google DeepMind, Meta, and J.P. Morgan, Finster is transforming how financial insights are discovered.

Built with intuitive technology, Finster translates user instructions into comprehensive briefs. It draws from high-standard global sources, such as earnings calls, reports, filings, and numerical data. Finster accelerates the research process by producing streamlined reports in a desired format, helping highlight opportunities, flag risks, and support confident investment.

Features

  • Customisable workflows: Analyst-directed, and can be adjusted to reflect each firm’s unique investment research processes.
  • End-to-end audit trails: Reports are exhaustively referenced, making it easy for analysts to fact-check and interrogate the findings with line-level and row-level attribution linked back to the source documents.
  • Rigorous corroboration: Compares findings across documents and competitors, tracks inconsistencies, and will alert the analyst if sources fail to pass the in-built credibility standards.
  • Extensive global data coverage: Combines premium data sources such as global earnings call transcripts, company fundamentals and estimates datasets from FactSet, with carefully curated and tagged SEC filings, annual reports, investor presentations, and sustainability reports.

Use Cases

  • Earnings Analysis: Extract custom insights from quarterly earnings and investor calls.
  • Completing custom sustainability reporting: Populate custom ESG reports with the latest information from various sources.
  • Uncover red flags earlier: Automatically scan filings, transcripts, financial statements, and news to uncover hidden red flags.
  • Identify thesis fit and catch thesis drift: Assess how and to what extent an investment idea fits a specified thesis.

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