RPA-in-insurance – Report


Rise of RPA & AI
in Insurance

Are you set on the road to RPA adoption, find out factors to consider during RPA implementation. Happy reading!

RPA promises to run 24/7 with no stops or breaks, minimizing human errors along the way. While RPA has several use cases including billing management, customer onboarding, data validation, customer service inquiry routing, inventory list updating, loan qualification and risk assessment, a lot of it still requires human intervention. This is where newer technologies are promising to take automation to the next level.

In recent times, RPA’s adoption as an automation approach has become mainstream and many companies have started looking at RPA as one of their key strategic investment areas. While the expectation is high on the RPA initiatives, about 30-50 % of the initial RPA projects fail due to existing siloes. As a sponsor of such an initiative, how can you increase the chance of a successful outcome?

In this technology report, we cover in detail on the approach you must consider to identify automation opportunities, how to identify use cases, factors that affect RPA implementation timeframes and more.

Key takeaways

Find out how RPA for insurance can not only reduce the workload and cost of operations but also frees up time and money to improve customer satisfaction

Complement RPA with ML solutions to enable expanding RPA to areas that have unstructured information or complex processing rules

Understand how the governance team plays a crucial role since RPA implementations cannot be technology driven nor can it be just business driven

Download the whitepaper

>50% of Insurance companies have started their RPA journey. Are you going to be left behind?