Financial Services AI Data Annotation

Financial Services

Data annotation that holds up to regulatory scrutiny

Synnth labels the documents, transactions, and communications behind fraud detection, credit risk, and compliance AI — with security and audit standards built for regulated financial institutions.

Overview

Financial AI has to work in an environment where errors are costly and data handling is regulated. Synnth annotates financial documents, transaction data, and customer communications with the security controls and domain expertise banking, insurance, and fintech teams require — encrypted handling, NDA-backed engagements, and annotators trained on financial terminology and regulatory context.

What we do

Data collection & annotation across every AI modality

From sourcing raw data to delivering production-ready labeled datasets — Synnth covers the full pipeline across the four core data types that power modern AI.

Data collection

Annotation

Document classification (statements, contracts, ID documents, claims forms)
Named entity recognition for financial text (amounts, parties, dates, account details)
Fraud signal and anomaly labeling
Sentiment and intent labeling for customer service transcripts
Regulatory compliance document tagging
Optical character recognition (OCR) validation and correction

Why Synnth for financial services

Every Synnth project follows the same structured pipeline, regardless of data type, language, or volume. That consistency is not bureaucratic — it is the mechanism through which we maintain quality at scale.

Security built for regulated data. All financial data is encrypted at rest and in transit, handled in access-controlled environments, and covered by NDA on every engagement — with processes aligned to ISO 27001 and GDPR requirements.

Domain-literate annotators. Labeling teams are matched to financial terminology and document types, reducing the ambiguity errors that generic annotators introduce into contract and claims data.

Fraud-pattern sensitivity. Annotators are trained to flag subtle anomaly signals in transaction and document data, with senior review on every fraud-labeling batch given the asymmetric cost of false negatives.

Auditable QA trail. Every batch carries inter-annotator agreement metrics and reviewer sign-off records — documentation your compliance team can actually use.

Delivery formats

2,000+ expert annotators, matched to your domain

JSON, CSV, or direct integration with your document processing or fraud detection pipeline via API.

Ready to build AI on data you can trust?

Whether you need a small pilot batch or an ongoing production annotation pipeline — tell us what you’re building and we’ll tell you exactly how we can help.

FAQs

Common questions

Everything you need to know before starting a AI Data collection or annotation project with Synnth.

💡 Can’t find your answer here? Talk to our team — we typically respond within one business day.

How is sensitive financial data protected during annotation?

All data is encrypted in transit and at rest, processed in access-controlled environments, and covered by NDA. Our processes align with ISO 27001 and GDPR requirements.

Can you annotate scanned or OCR'd financial documents?

Yes, including OCR validation and correction as part of the annotation pipeline for scanned statements, contracts, and forms.

Do your annotators understand financial and regulatory terminology?

Yes. Financial services projects are staffed with annotators trained on financial document types and terminology, not generalist labelers.

Get started

Start your AI Data collection or annotation project today

Tell us your use case, action taxonomy, environment, and volume. Our team responds within one business day with a scoping plan and no-obligation quote.