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Today most insurance companies know about Robotic Process Automation (RPA). RPA has been in the market for 20 years and insurance companies now have in-house automation teams trained to build and maintain such robots themselves directly. Yet, only a few know about Conversational Process Automation (CPA).
So, in this week’s blog, we answer the questions: what is CPA? What is the link between RPA and CPA? Most importantly: how can they be deployed into a cohesive automation strategy?
What is RPA?
RPA appeared in the market in 2003 with Blue Prism's first commercial product, “Automate”. Since the appearance of this technology, the execution of back-end processes changed drastically.
RPA is an application of technology aimed to improve business processes through automation. It normally leverages robots that automate the tasks of existing processes. This ultimately reduces process inefficiencies and improves their performance at a fraction of the cost. The business processes here are middle and back-office processes.
Such robots also eliminate unnecessary human manual input in various steps of the business process. They are usually applied to execute low-value high-volume, repetitive and routine tasks. Every process that is not too complex, well-understood, and well-documented with local rules makes a good prospect for automation.
RPA relies upon structured data inputs; clear input will trigger a waterfall of automated tasks. As such, RPA has achieved stellar results in regard to saving costs on the execution of the middle and back-office process.
Despite this, RPA has a glaring limitation: very often business processes start with customer-facing interactions. This often translates into unstructured data that RPA is not able to handle.
This is precisely why CPA was born.
What is CPA?
Conversational Process Automation (CPA) made its appearance in the last five years. It focuses on the automation of front-end customer-facing processes. This often implies the use of expert chatbots to enable a personal conversational experience at scale.
It can be seen as the complementary solution working in symbiosis with RPA since it is able to:
- Execute insurance specific customer-facing processes in a compliant way
- Interpret and understand the customer’s unstructured input
- Structure it and wrap it into a format digestible to robots (e.g. RPA itself) or back-end systems directly
CPA is a learning solution that not only captures the customer input but also analyses it and informs businesses over the performance of the process with customer insights. This allows the generation of business intelligence while giving the means to quickly adapt to changing customer expectations through an evidence-based approach grounded on real data.
CPA: the ideal interface between customers and insurers' back-end systems
A key focus for 2021 is continuing the automation of processes in insurance companies. These started from the back-office and are progressing towards the customer-facing side to enable customers to self-serve directly. CPA is the critical component to support this strategy as it complements RPA and the system. As data from customer-facing processes is often unstructured, CPA generates conversation analytics that gives the relevant knowledge to insurance companies for continuous improvement.
Businesses and customer expectations have evolved far beyond. Going by design, CPA has the ability to meet both present and future needs.