As a large financial services organisation, Royal London managed sensitive financial data and high-risk transaction flows. Despite ongoing investments, cyber controls were fragmented across legacy applications, identity models varied between business units, and audit findings highlighted gaps in access governance, endpoint protection and incident response readiness. Executives were concerned about regulatory exposure, reputational risk and...

Royal London operated multiple siloed data sources across pensions, savings and operations. Reporting was manual, inconsistent and difficult to trust. Leaders across Finance, Operations and Risk struggled to get timely insight, affecting forecasting, regulatory reporting, fraud monitoring and customer performance analytics. The Board wanted to shift the business toward evidence-led decision making, but lacked a...

Across global payment channels, fraud and anomaly cases were rising in volume and complexity. Existing controls were rule-based, reactive, and created false positives that slowed customer transactions and increased manual investigation workload. Fraud losses and operational cost were a Board-level concern, and regulators demanded improved controls, auditability and faster intervention.

Engineering productivity across global teams was being held back by fragmented tooling, inconsistent documentation, slow onboarding, and unclear ownership of APIs and services. New engineers took weeks to become productive, and support teams were overwhelmed with repeated questions. Leadership wanted transformation without adding more layers of process — something scalable, self-service, and trusted across regions.