Finster FAQs

Finster is an AI-native platform built specifically to meet the rigorous demands of the financial services industry. If you would like to learn more and explore how Finster can transform your team, please reach out to schedule a demo.

1. What makes Finster specifically built for finance professionals?

Finster is an AI-native platform, built from the ground up for financial research. It integrates data ingestion, structured search, and output generation in a single pipeline without relying on plug-ins or manual summaries.

Finster focuses on front-office workflows in investment banking and asset management. It pulls data directly from primary sources including earnings calls, filings, investor relations sites, and providers like FactSet and Crunchbase. 

Using Finster, analysts can automate common tasks such as creating pitch decks, investment memos, strip profiles, comps sheets, and earnings summaries. Outputs are tailored for the needs of finance, with sentence-level citations and real-time updates. Built for transparency and auditability, with a near-zero hallucination risk, Finster will say when the data is not available.

Privacy and trust are at the core of everything we do. Finster offers enterprise-grade security as standard. For mid to large institutions, we can offer single-tenant or virtual private cloud deployments. Finster is SOC 2-compliant and can connect securely to internal systems, with no training on proprietary data.

Institutions can customise tone, output format, permissions, and best practices to help train and guide their analysts. User-level personalisation is handled using Finster’s proprietary methods, with no training of shared AI models. All personalisation can be removed on request.

The team brings together extensive AI experience from leading organisations such as Google DeepMind, Meta AI, and Amazon, alongside strong financial expertise from institutions like J.P. Morgan, Rothschild & Co, and Aviva Investors.

2. How does Finster compare to other generative AI tools?

Finster is purpose built for institutional investors and investment banking teams. We incorporate high quality, real-time data sources, sentence-level citations, and secure private deployments. General purpose AI tools lack the accuracy, transparency, and controls required by financial firms - Finster solves for this.

3. Can I trust Finster’s information?

Yes. Every fact is cited down to the sentence level or to a cell in a table. Finster pulls from primary sources such as SEC filings and Investor Relations documents from thousands of global companies and complements it with data from premium data providers such as FactSet, Morningstar and Crunchbase.. If it cannot verify a fact, it does not return one.

4. Is my data safe with Finster?

Yes. Finster does not train on user data. We are SOC-2 certified and have a range of deployment options to suit your company's needs. Please see our Security Page for more details.

5. What makes Finster AI-native, not just AI powered?

Finster was built AI-first, not adapted later. Unlike wrappers or bolt-ons, it was designed from the ground up to automate entire research workflows. Data is ingested, tagged, and structured at the source, then retrieved and used in generation within a single system. This removes manual steps and avoids layering AI onto legacy tools.

At the core of Finster’s performance is its proprietary AI agent framework and granular citations. These power its accuracy, reliability, and ability to push the boundaries of what AI can do in front-office finance tasks.

6. What types of data does Finster use?

Finster combines data from FactSet, Crunchbase, and Morningstar with primary sources such as SEC filings and documents from Investor Relations sites. Finster processes documents from thousands of global companies' Investor Relations sites, including Small and Mid Caps, to ensure users can get answers grounded in accurate and up to date data. Users can also upload internal files securely and privately, they can then use Finster to search across public and internal filings.

7. Can I access private company data in Finster?

Yes. Finster includes private market data through its partnership with Crunchbase. Analysts can screen private companies, run comps, and build outputs using this data, with full source traceability.

8. Can Finster say it doesn’t know?

Yes. Finster is designed to pull all relevant facts and explain what it has, and what it doesn’t. If the data is incomplete or unsupported, it will return “no answer.” Every fact is sourced and cited, so the chance of hallucination is close to zero. Users don’t need to double-check every output.

9. How does Finster ensure data traceability?

Finster cites every figure at sentence level. Users can click to see the source, date published, and full document context.

10. Can I use Finster with my internal files?

Yes. Finster supports uploads of memos, slides, reports, and internal data. Files stay private and secure, with no cross-client access.

11. What workflows can I complete in Finster?

Finster supports analysis, comps, modelling, screening, earnings reviews, strip profiles, pitch decks, CIMs, client briefings, company and industry primers, and risk reviews and much more. If you want to explore Finster's capabilities, reach out and book a demo.

12. How is Finster different from Bloomberg or CapIQ?

Finster is AI-native. It was built to automate research workflows from ingestion to output. Unlike traditional terminals, it handles complex tasks end to end, not just data lookup or file summarisation.

Finster’s architecture is optimised for accuracy, insight, and speed. It reads filings, transcripts, and market data directly. It extracts figures, flags risks, and generates structured outputs with full source traceability.

Finster also delivers best-in-class citations and detailed tagging, even across small and mid-cap companies often missed by other platforms. This helps teams build deeper views of undercovered names.

Finster acts as the intelligence layer for financial research, built on a strong data layer from leading providers and proprietary sources.

13. How is Finster different from ChatGPT?

Finster is purpose-built for institutional investors and investment banking teams. Unlike ChatGPT, which uses general web content, Finster integrates premium financial data providers like FactSet, Morningstar and Crunchbase, along with SEC filings, investor websites, and internal datasets. It combines real-time market data with reference data and curated content to ensure high data quality.

Finster is designed to automate research workflows, from company analysis and comps to risk scans, earnings summaries, and first-draft materials. Every output includes granular citations, often down to the sentence or table cell, with clear sourcing and no guesswork. When data is missing, Finster says “I don’t know.”

It has enterprise-grade security, including private cloud deployment, strict data isolation, and no training on client inputs. Finster also adapts to your internal tone, templates, and permissions framework.

14. Is Finster customisable for my team or institution?

Yes. Finster allows customisation at both the institution and user level, with privacy and control built in.

Institutions can create custom Task templates to guide analysts through complex workflows like drafting initiation reports, creating strip profiles, or spreading comps. This helps embed best practices directly into day-to-day work.

Users can personalize outputs through ongoing use. Finster does not train on user data, so preferences stay private.

For deeper control, Finster also supports institution-specific fine-tuning using reinforcement learning from human feedback (RLHF).

15. Does Finster support non-equity research workflows?

Yes. Finster is used for public markets users across equities, credit, ESG and macro, and across private markets for investment banks and private credit funds. Screens and outputs adapt to asset class and sector.

16. Can Finster be deployed in a private environment?

Yes. Finster supports single-tenant and virtual private cloud containerised deployments. Finster is SOC 2 compliant and all data is encrypted in transit and at rest.

17. Does Finster have global data coverage?

Yes, Finster has full global data coverage both through data partnerships and Finster's proprietary data curation pipeline that pulls investor presentations, sustainability reports and much more from thousands of global public companies. We have full SEC filings coverage, but where Finster data coverage is truly best-in-class is Europe, India and wider APAC, where we have deep data coverage of Small, Mid and Large Caps. We can also add any public company IR documents at client request.

18. Can Finster export to Excel or PowerPoint?

Yes. Users can export directly to branded templates used by their team with granular control over output structure and formatting.

19. Can I use my own LLM with Finster?

Yes. Finster is LLM agnostic. Clients can use their own LLM API keys if preferred.

20. How fast is Finster compared to legacy tools?

Finster helps teams perform end-to-end tasks that previously took hours in minutes and ad-hoc analysis that previously took tens of minutes in seconds.