Robotic process automation (RPA) has moved from an emerging technology to a widely deployed solution across insurance. Over 60% of property/casualty and 70% of life/annuity/and benefits insurers now use RPA in production or pilots. The appeal is clear: RPA provides quick wins and significant lift by automating manual, data-intensive processes like legacy system data transfers and manual submission entry.
Ideal use cases for RPA are often short-term fixes lacking long-term strategic value, such as bridging legacy systems during upgrades. RPA can also help manage legacy systems that must be perpetually maintained. For life insurers, RPA may replace integration long-term for closed books. The technology generates lift rekeying data between disparate systems and during new business processing.
However, RPA doesn’t provide true integration or flexibility of modern cores. Over time, it can create technical debt and complexity that inhibits innovation and customer experience.
When implementing RPA, insurers need intentional governance and operating models to contain “bot sprawl.” A decision framework can guide use cases, balancing short-term value and long-term risks. The goal should be eliminating manual processes rather than perpetuating them with bots. Insurers should have a plan to eventually sunset many RPA deployments as part of overall transformation efforts.
RPA is a valuable tactical solution that generates quick wins. However, integrated API-enabled core systems will better position insurers for growth, risk management, and meeting demands. With the right approach, RPA can optimize operations today while serving as a bridge to more strategic modernization down the road. The technology is best leveraged not as a permanent fix but as part of the journey.
For more information on successfully deploying RPA, check out Datos Insights’ recent report, Effective RPA Implementation: An Insurer CIO Checklist, or contact me at [email protected].