Financial Industry
Fraud & Identity Theft Protection, an Enterprise Sovereign AI Use Case
Challenges:
- Financial organizations can typically only use about 25% of transaction data for fraud prevention analysis.
- This transaction data contains sensitive or personally identifiable information.
- Legal, compliance and other challenges lead banking organizations to fill the gap with synthetic data in order to build and train models for better fraud and identity theft protection
Our Solution:
- Olympus AI delivers infrastructure for building AI models using various pre-built and custom services
- We provide confidential computing and privacy solutions that encrypt and protect sensitive data in use for training or inference
- Olympus AI enterprise sovereign AI infrastructure allows financial organizations to build models that use real and sensitive data for higher accuracy without compromising confidentiality
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We build AI solutions to address your financial organization's custom use cases.
Anti-Money Laundering (AML) Model
Our Solution:
- Olympus AI offers confidential AI training as infrastructure or as a single appliance that can be deployed at a private data center
- This allows participating banks to use our confidential AI training solution without exposing sensitive data and without the algorithm IP being exposed
- Non-sensitive results are shared to the aggregate model and used to train the final model
