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Documents, risk and claims

AI Data for Finance and Insurance

Regulated workloads need annotation that is accurate, explainable and handled under controls you can evidence.

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Accuracy You Can Evidence

In financial services the question is never only "is the label right" — it is "can you show how it was decided, by whom, and under what rule". We run these programmes with the access controls, audit trails and reviewer separation that a compliance conversation requires.

Where Finance & Insurance AI Programmes Struggle

The data is personal

Documents contain exactly the information that must not leak.

Decisions must be explainable

A model outcome that cannot be traced to its training basis is a regulatory problem.

Class imbalance is extreme

Fraud is rare, and rare classes are where naive sampling fails.

Formats never settle

Every institution, and every year, brings new document layouts.

AI Use Cases We Support

Document understanding

KYC, statements and contracts with field-level extraction.

Claims processing

Damage assessment from photographs and claim-form structuring.

Fraud pattern labelling

Confirmed-case annotation for imbalanced training sets.

Risk and credit features

Structured annotation of applicant and transaction records.

Customer communication

Email, chat and call classification for intent and compliance.

Redaction and PII detection

Locating personal data for masking pipelines.

Data Types We Handle

  • Scanned and digital documents OCR plus field and table extraction.
  • Transaction series Labelled histories with confirmed outcomes.
  • Claim photography Damage classification and severity grading.
  • Text and voice Communications classified for intent and risk.

How We Run the Programme

  • Least-privilege access Annotators see only what their task needs, on controlled environments.
  • Separated review The reviewer is never the labeller, and both are recorded.
  • Written decision rules Every ambiguous class has a rule an auditor can read.
  • Retention on your terms Data lifetime is agreed at the start and enforced, not assumed.

Build Finance & Insurance AI on Data You Can Trust

Tell us what you are building and we will come back with a plan, a sample and a price.

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