How Simfuni Migrates 270 Million Legacy Life Policies to Automate Back-Office Servicing

Why It Matters

Scaling migrations off legacy systems addresses a major operational and cost burden in life insurance, unlocking AI-enabled automation that can materially reduce expenses, lower risk, and improve customer service across a vast, previously hard-to-modernize book of business.

Summary

Simfuni (Syntoni) is helping life insurers migrate roughly 270 million legacy closed-book policies onto its platform to automate labor-intensive back-office servicing and modernize technology stacks ahead of an AI-driven wave. The company positions the migration as a necessary step for carriers—many of which missed earlier cloud transitions—to implement controls, reduce operational risk, and deploy new automation and AI tools. By automating policy servicing, Simfuni aims to cut hundreds of millions in manual servicing costs and deliver faster, higher-quality customer interactions. The firm also highlights industry events like Scout as valuable forums to engage large carriers about product fit and priorities.

Original Description

Traditional life insurance providers are eager to capitalize on modern artificial intelligence, yet a significant portion of the industry missed the cloud computing era entirely, leaving their core data locked inside high-risk legacy systems. In this interview from the Scout InsurTech event, Shaun Quincey, Co-founder & CEO at Simfuni, discusses the foundational infrastructure overhauls required to get carriers "match fit" for modern automation.

Quincey breaks down a massive structural bottleneck within the domestic market, noting that over 270 million life insurance policies remain trapped on rigid, closed-book legacy systems that drain hundreds of millions of dollars through manual customer servicing. He outlines how Simfuni solves this operational drag by serving as a secure migration platform that transfers closed books into an automated, digital cloud layer. Discover how eliminating manual paper-shuffling allows forward-thinking insurers to remove core systemic risks, lower administrative costs, compress transaction turnaround times, and establish the clean data foundation required to safely run advanced AI utilities