Banking, finance and insurance
Precision where the margin of error is regulated
Financial services combine large data volumes with strict documentation requirements. Arktis AI is developed for workflows where every step must be explainable afterwards.
Focus
Automated claims handling, risk analysis and compliance.
Benefit
Developed with DORA and European operational-resilience requirements in mind.
Key challenges
- Manual processing of claims and supporting documentation.
- Requirements for traceable documentation at every step.
- Sensitive customer data that cannot leave controlled environments.
- Regulation that changes faster than internal routines.
Example workflow
- Documentation is received and classified.
- The model structures the content into defined fields.
- Deviations and uncertain fields are flagged rather than guessed.
- A case handler verifies and approves.
- The result is written back to the source system with a log entry.
Data and control requirements
- Separation of customer data and training data.
- No customer data used for training without an explicit agreement.
- A complete event log.
- Defined operational-resilience controls.
Technical integration
- API in private or European cloud.
- On-premise for restricted environments.
- Role-based access and event logging.
Relevant use cases
Structuring claims
Extracting fields, amounts and dates from submitted documentation and making them machine-readable.
Input for risk assessment
Collecting relevant information from multiple documents into a single readable basis.
Compliance review
Comparing internal documents against current policy and flagging deviations for review.
The model's role
The model prepares and structures. It does not decide claims, creditworthiness or liability.
Human oversight
Decisions with financial consequences for a customer always require a human control point.