What are some key technologies mentioned in the chapter that help safeguard sensitive data in financial services?

Key technologies mentioned for safeguarding sensitive data in financial services include homomorphic encryption and federated learning. Homomorphic encryption allows data to be processed in its encrypted form, ensuring customer privacy during AI model training. Federated learning keeps data on customers' devices, preventing it from being shared with central servers, thus reducing the risk of data breaches.

The chapter highlights the importance of advanced technologies in protecting sensitive customer data within financial services. Homomorphic encryption enables financial institutions to process data without decrypting it, maintaining privacy while improving AI models. Federated learning further enhances data security by ensuring that sensitive information remains on the customer's device, thereby minimizing the risk of unauthorized access and data breaches. These technologies are crucial for compliance with privacy laws and for building customer trust in AI systems.