Building Privacy-Preserving ML for CRM Systems With Federated Learning

The creation of machine learning models for lead scoring is often hindered by the distribution of customer data across different regions, including the EU, US, and APAC. The General Data Protection Regulation (GDPR) prohibits the transfer of EU data to central servers, making traditional approaches to model training ineffective and potentially costly. Traditional methods, such as centralized training, separate regional models, and data replication, are either non-compliant or result in poor model performance. Federated learning offers a solution by allowing models to be trained in each region and sharing only model updates, rather than raw data, thereby addressing data residency concerns and enabling cross-regional learning.