Legacy insurance systems cost insurers up to $5 million annually in hidden operational costs, according to an INTX Insurance Software research report, "The Cost of Legacy Insurance Software Systems: Wasted Time & Money." The report, conducted by RSM, surveyed over 250 insurance professionals and also found that legacy platforms require internal IT support that add up to nearly 900 hours –or $450,000– in lost productivity.
"Our research uncovered how legacy core insurance systems are creating structural inefficiencies that translate into avoidable costs and lost productivity across the industry. These inefficiencies are no longer abstract," said Lara Colestock, director of human-centered design at RSM. "Outdated systems are creating real economic drag by slowing operations, increasing costs, and limiting insurers' ability to adapt. The study reinforced that it's a strategic necessity to modernize core systems for efficiency, agility, and long‑term competitiveness."
Data latency, a result from manual intervention of policy workflows, can cost insurers $1 million or more, according to the study. Most, 72%, of insurance organizations rely on Excel or internally built tools to manage critical insurance workflows, and 52% of policy administration processes require manual intervention. More than one-third, 36%, of survey respondents identified quoting, policy issuance and claims processing as the top areas that require manual intervention.
Insurers are spending between $475,000 and over $1 million on employee costs annually for "time-consuming or unnecessary" manual work, according to the report.
"Insurance leaders have spent decades accepting inefficiency as the cost of doing business. The reality is that legacy core systems have quietly normalized millions of dollars in operational waste across the industry," said Rob Lewis, CEO of INTX Insurance Software. "When more than half of critical workflows require manual intervention and implementation cycles stretch beyond a year, that isn't just a technology problem- it's an operating model problem. The next generation of insurers will be defined by those willing to challenge that status quo and modernize the core of their business."
INTX's study also suggests that while fragmented legacy systems continue to limit insurers' ability to deploy advanced analytics and AI-driven decision making, the high costs to implement new systems is a challenge for many. One-third reported spending over $500,000 to implement a single core system, and most operate at least two or three systems totaling expenses as high as $3 million. Almost half, 45%, of organizations noted implementation timelines of 18 months or longer.
However, INTX's research indicates emerging insurance platforms can address these challenges for insurers.
"Much of the industry's high implementation cost stems from attempting to layer modern analytics and AI onto fragmented legacy systems that were never designed for real-time, enterprise-wide operations. Insurers often spend more time integrating platforms and reconciling inconsistent data than deploying the actual decision tools, turning modernization into multi-year engineering programs with limited near-term business impact. As a result, AI initiatives frequently operate on incomplete or delayed information and struggle to influence frontline underwriting, claims, and pricing decisions," said Lewis. "Emerging insurance operating systems address this by establishing a unified operational and data foundation, allowing AI to be embedded directly into core workflows rather than functioning as an external add-on. This enables faster deployment, lower risk, and measurable improvements in both operating efficiency and loss performance, creating a clearer path to structural improvement in Combined Operating Ratio rather than incremental gains."
Lewis added, ""The industry's implementation challenges aren't caused by AI or analytics- they stem from trying to bolt modern capabilities onto legacy infrastructures that were never designed for real-time, enterprise-wide operations. Insurers often spend more effort integrating systems and reconciling data than deploying the tools intended to improve performance, which turns modernization into a costly, multi-year engineering exercise with limited near-term impact. The new generation of insurance operating platforms changes that dynamic by unifying core functions and data into a single operational foundation, allowing AI to be embedded directly into underwriting, claims, and pricing workflows. This enables faster deployment, lower risk, and tangible improvements to both expense and loss performance. Ultimately supporting structural gains in Combined Operating Ratio rather than incremental efficiencies."
