What was the impact of the AI solution?

Saved customers in poorer neighborhoods nearly half a million pounds in ATM fees within six months. Reduced fraud. Improved overall customer wellbeing.

Source

ProductionEvidence: Medium55/100

NatWest personalizes customer experience using machine learning on AWS (Amazon SageMaker)

Use case typeFraud detectionUpdated Jun 13, 2026

NatWest Group is one of the largest banks in the United Kingdom. The company uses its legacy data to innovate and personalize personal, business, corporate banking and insurance services for 20 million customers. NatWest has deployed nearly 100 machine learning models on Amazon SageMaker to drive personalized messaging and customer engagement across its banking and insurance experiences.

Organization: NatWest Group
Industry: Finance
Location: United Kingdom
Published: May 2026

Reported outcomes

Strategic outcomes

Customer experience & trustPersonalized banking and insurance experiencesRisk & complianceReduced fraudCustomer experience & trustImproved customer wellbeing

Why do we believe this deployment?Customer identity, provider attribution, maturity, and source checks

Customer: NatWest Group
Provider: AWS
Maturity: Production
Linked source: AWS

NatWest has deployed nearly 100 machine learning models on Amazon SageMaker to drive personalized messaging and customer engagement across its banking and insurance experiences

Customer identity supportedSource describes one deploymentMaturity supported

Primary read

Use case focus

Showing 3 of 3

1Customer Personalization
2Fraud Detection
3Customer Analytics

Personalize messaging for about 20 million customers while improving customer outcomes and reducing fraud and fees by leveraging legacy data.

NatWest Group deployed nearly 100 machine learning models using Amazon SageMaker to power personalized messaging and data-driven customer engagement across banking and insurance experiences.

Technologies

Amazon SageMaker