Helping you maintain regulatory compliance
Privacy-preserving ML across organizational boundaries
Data teams in regulated industries, such as financial services, insurance, and healthcare, are transforming how they manage risk by leveraging machine learning and advanced analytics. Apheris allows you to access high quality data from your suppliers, customers, and partners in a secure and privacy-preserving way across organizational boundaries.
EXAMPLE USE CASES
Credit risk management
Train robust and interpretable ML models on third-party consumer data to assess credit risk. Integrate your existing model and data pipelines for validation and QA to ensure you comply with regulation.
AI risk management
Organizations that adopt AI and ML are heavily investing into their AI risk management capabilities. Leverage Apheris for responsible and privacy-safe use of data. Develop fair and trustworthy AI systems through secure access of data that spans across boundaries.
Cross-border data analysis
Work collaboratively across borders while ensuring compliance with privacy regulation and residency requirements. Integrate Apheris into your ML workflows and ensure that data stays protected and never moves across borders.
Why risk modelling teams choose Apheris
Data never needs to move
The Apheris federated infrastructure ensures that data always stays where it resides and under the full control of the data custodian, meeting data residency requirements.
ML teams can leverage their existing ML and data pipelines to ensure that models are trustworthy, robust and interpretable.
The Apheris platform provides logging of every interaction to assist with compliance and audit obligations.
Apheris offers state-of-the art security, privacy, and governance to ensure compliance with industry and privacy regulations including GDPR, CCPA, HIPAA, and more.
Private, secure, governed ML
Want to learn more about how Apheris can help you safely productize your data assets?