Fixed failing batch jobs and increased throughput by 55% for a major UK insurer

Client profile
Customer since – 2021
Number of employees – approx. 10k
Sector – Financial Services

A major UK insurer covering millions of lives was struggling with a problem familiar to many organisations with mainframe-era systems: critical overnight batch processing that routinely pushing against operational limits.

The insurer’s legacy platform could reliably support only around 70% of required capacity, making peak periods such as renewals especially fragile. Long-running jobs were prone to timeouts, causing downstream delays and overnight callouts for operations teams. When failures occurred, recovery took hours, with equivalent windows of potential data loss—an unacceptable exposure for a regulated business reliant on timely, predictable processing.

The organisation partnered with Version 1 to modernise its processing workloads on AWS

Migrating service to AWS to improve throughput, stability, and recoverability.

We redesigned the processing model based on size and complexity of the workloads using AWS Lambda, Fargate and RDS, cutting recovery times from hours to minutes.

Decoupled workflows and messaging introduced clearer visibility and eliminated brittle “big bang” overnight runs. The crucial governance, security, and guardrails were embedded throughout using native AWS services.

Delivering proven, measurable impact

The transformed platform delivered a 55% increase in throughput and achieved 100% batch success across critical workloads. Availability improved to nearly 99.96%, with recovery times of about 12 minutes and data loss reduced to roughly three minutes.

With infrastructure defined as code, the insurer now has a repeatable blueprint for modernising additional workloads.

By modernising its engine room, we were able to turn batch processing from a persistent risk into a high-performing, dependable capability. The insurer is now able to grow confidently, delivering a better service.