Case Study: Ladder achieves real-time, scalable underwriting in minutes with Confluent

Ladder Puts Data in Motion to Underwrite Policies in Minutes

Ladder, a direct‑to‑consumer life insurer, needed to accelerate underwriting so customers could apply for and activate policies in minutes using machine learning fed by continuous third‑party data. To address scalability, reliability, and ops overhead from a self‑managed Kafka deployment, Ladder selected Confluent’s managed event‑streaming platform (managed Kafka) to power its real‑time data flows to the ML underwriting engine.

Confluent helped migrate producers and consumers (using Replicator), provided Control Center for monitoring, and supported Ladder in encrypting data in transit; the move eliminated Kafka‑related outages, achieved five nines reliability, completed the switchover in minutes with no user downtime, reduced administrative overhead, and delivered rapid ROI—letting Ladder focus engineering on customer experience and scale automated underwriting.

Ladder

Nick Hansen

Software Engineer and Platform Team Lead