AIA Hong Kong and Macau builds a centralized lakehouse for personalized insurance recommendations
AIA Hong Kong and Macau migrated from a rigid on-premises Oracle data warehouse to Azure Databricks to build a centralized lakehouse, using MLflow to manage the machine learning lifecycle and support personalized recommendation models. The initiative supported more than 11 ML projects and contributed to double-digit growth in customer lead generation and 2x+ growth in customer engagement and financial advisors' lead generation.
Overview
AIA Hong Kong and Macau migrated from a rigid on-premises Oracle data warehouse to Azure Databricks to build a centralized lakehouse, using MLflow to manage the machine learning lifecycle and support personalized recommendation models. The initiative supported more than 11 ML projects and contributed to double-digit growth in customer lead generation and 2x+ growth in customer engagement and financial advisors' lead generation.
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Inspect the highlighted sourceThe challenge
AIA Hong Kong and Macau's legacy on-premises Oracle data warehouse was structurally difficult to maintain and could not scale to process the growing volumes of structured and semi-structured customer data, leaving data siloed and blocking the holistic, 720-degree view of customers needed to deliver personalized insurance recommendations and financial advice.
The solution
AIA built a centralized lakehouse on the Azure Databricks Data + AI Platform to unify data engineering, analytics and machine learning, using MLflow to manage the full machine learning lifecycle and develop personalized recommendation models that combine internal customer data with external behavioural data for a 720-degree view of customers.
Reported business value
The lakehouse has driven more than 2x growth in customer engagement and more than 2x growth in financial advisors' lead generation, supported the development of more than 11 ML projects, and given financial advisors a 720-degree view of customers so they can recommend the right insurance products to the right customers.
Sources
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