At finotate, our leadership team brings decades of cross-disciplinary experience spanning global finance, economics, law, accounting, and data science. Educated at institutions such as Harvard, Princeton, and other top universities, they have held senior roles at Wall Street firms, global financial institutions, and leading academic centers—offering deep insight into the structure, context, and implications of complex financial and regulatory data.
About Us
We deliver research-grade data annotation for financial filings, regulatory disclosures, and economic reports, where accuracy, context, and domain insight are non-negotiable. Our annotation teams are composed of highly qualified professionals with advanced training in:
- Accounting and corporate finance
- Law and regulatory compliance
- Economics and public policy
- Data science and computational social sciences
Every project is guided by a rigorous methodology and multi-tiered review process, ensuring that our labels don’t just identify text, they capture its precise meaning and implications.
What We Annotate
We handle a range of financial and regulatory documents, including the following.
SEC Filings
(10-K, 10-Q, 8-K, DEF 14A)
Earnings Calls & Transcripts
Debt Contracts and Covenants
Structured Product Disclosures
Prospectuses and Offering Circulars
Annual Reports and MD&A
Research Reports and Broker Commentary
Policy Documents and Legal Briefs
Credit Agreements and Bankruptcy Filings
ESG Disclosures
Satellite images
Unstructured data (news, forum discussions)
Use Cases We Support
Whether for machine learning, compliance tools, or empirical research, our data is structured, validated, and ready to deploy across use cases such as:
Machine learning training pipelines
NLP fine-tuning (NER, relation extraction, summarization)
Quantitative text analysis in finance research
Risk, ESG, and compliance analytics
Credit scoring & underwriting models
Sentiment, tone, and policy signal extraction
Technical Delivery & Integration
We don’t just label data, we deliver it ready-to-use for:
- Machine learning pipelines (NER, relation extraction, summarization)
- Quantitative research (event studies, panel datasets)
- Natural language search/retrieval
- Regulatory risk/compliance platforms
Our datasets are:
- Schema-aligned, built according to your ontology or taxonomy.
- Structured, in JSON, CoNLL, CSV, XML, or database-ready formats
- Cleaned & normalized, consistent entity linking, dates, and labels
- Version-controlled, for reproducibility and traceability
Whether you’re building a financial LLM, trading model, or compliance tool, we ensure your data is accurate, structured, and deployment-ready.
Why Choose Us
Our leadership team includes senior professionals in finance, economics, law, accounting, and data science, holding Master’s and Doctoral degrees from Harvard, Princeton, and other leading global institutions. Together, we bring decades of combined experience across Wall Street, global financial institutions, academia, and hands-on annotation of financial, economic, and regulatory disclosures.
Our annotators are qualified professionals—Chartered Accountants, corporate lawyers, economists, and NLP engineers—trained in project-specific taxonomies and regulatory frameworks to ensure precise, consistent labeling.
We’ve delivered labeled datasets for academic research labs, fintech and regtech companies, hedge funds, private equity firms, and data vendors seeking research-grade annotation.
Every project begins with a review of the relevant laws, accounting standards, and disclosure requirements. This ensures our annotations are not only accurate, but also compliant with the intended regulatory context.
Annotations go through structured, multi-stage review by multiple domain specialists. This layered process guarantees the data is accurate, reproducible, and ready for AI training, compliance workflows, or empirical research.
From financial filings and economic reports to legal rulings and corporate contracts, we build annotation pipelines tailored to your data type, use case, and required output format.
Our Process
How We Work
-
Onboarding Call:
We align on goals, formats, and guidelines. -
Pilot Project:
You evaluate quality before scaling. -
Annotation at Scale:
We assign a domain-trained team with QC processes. -
Delivery:
Clean, validated, and structured output in your preferred format.
Who We Work With
- AI startups building fintech and regtech solutions.
- Hedge funds and asset managers building proprietary datasets.
- Academic researchers conducting empirical financial studies.
- ESG and compliance teams extracting signals from reports.
- NLP teams fine-tuning LLMs on domain-specific corpora.