How insurance companies benefit from Robotic Process Automation (RPA)
Digital transformation has been reshaping the way whole industries are doing business and the insurance industry is no exception. A big part of that transformation is looking at the ways in which many of the tasks that take up valuable employee time can be performed more cost-effectively and efficiently with automation. One way this can be achieved is through Robotic Process Automation (RPA), sometimes referred to as "RPA bots" or simply "bots". RPA is built upon a combination of technologies including machine learning (ML), natural language processing (NLP) and workflow automation.
In its earliest iterations, RPA was used primarily for automating relatively simple and repetitive tasks. However, with improvements in optical character recognition (OCR) and when combined with AI, it becomes even more powerful. This supercharged version of RPA is sometimes referred to as cognitive RPA (CRPA).
In recent years companies have been investing significantly in RPA. A 2019 KPMG study found that it was seen as the second most important technology driving digital transformation after the Internet of Things (IoT), with the market for RPA expected to be worth almost USD$8.7B by 2023.
What are some of the key areas in which the insurance industry is using RPA?
The insurance industry is already seeing success using RPA in a number of ways including:
Claims processing is the most common use of RPA in insurance. The ideal scenario is to be able to manage the entire process from the first notice of loss (FNOL) to the payout of a claim. With traditional insurance companies this is not always easy as sometimes processes still require receiving written FNOL, that would need to be scanned and have data recorded manually before entering the RPA process stream. On the extreme other end of the spectrum, digital native insurtech company Lemonade, utilized their RPA process to process and pay a property theft claim in an astounding three seconds.
Creating and administering policies is a time intensive process and can be sped up significantly by utilizing RPA in a number of ways such as collecting registration information from customers, researching and collecting information for underwriting, analyzing customer emails. It can also be used to cancel policies quickly and efficiently.
Insurance is one of the most heavily regulated industries and an advantage of utilizing RPA in business processes is that bots, unlike humans, will not make errors in the work as long as they are provided accurate data to begin with. RPA will always follow a defined set of rules, which means that no compliance requirements will end up missed or incorrectly completed. Not only that, but because all RPA actions are logged it becomes easy to audit if needed at any point.
Taking it to the next level – RPA and AI combined to create intelligent automation
Where RPA stands to make the greatest impact in the future is when it is combined with AI and is able to move beyond just following a defined set of rules and exercise a degree of decision making, something once only possible with human interaction.
This cognitive RPA allows for more intelligent automation that can work with customers across all of the channels in which they interact with an insurance company using the system, whether it is voice, SMS, web or a mobile app. Intelligent chatbots with NLP abilities can interact with customers 24/7, and could be used for an end-to-end automation of claims processing and more.
In the case of an auto insurance claim a scenario might involve a chatbot utilizing conversational AI to interact with a customer to collect all necessary identification and information. This information, including images can then be processed using OCR and then the claim can be handled by the standard RPA systems in place. Any exceptions can still be handled by a human agent as necessary. Even better, these systems can be trained on the human handling of exceptions, allowing them to learn from them and apply it to future decisions. The company benefits from a streamlined cost-effective system, and the customer has the benefit of no wait times for a customer service representative and faster processing of their claim.
What are some obstacles in implementing RPA in the insurance industry?
While RPA has been demonstrated to achieve some significant outcomes for the industries using it, one lesser discussed issue is the relatively high failure rate of 30-50% of initial attempts to implement it according to a report by Ernst & Young. To avoid contributing to these failure statistics, when getting started with RPA implementation in the insurance industry it is important that companies identify smaller projects to tackle first rather than try to automate everything at once.
A feature of RPA is that it can generally be implemented in a low-code/no-code way. This can give the impression that it requires less skill to set up, leading to potential issues. Working in a no-code manner can speed up the implementation process, however, sometimes something as small as a UI change in the company software can bring the system crashing to a halt. Because of this, it is always worth considering working with an experienced RPA implementation partner that can understand where these issues can arise and how to avoid them.
Another major selling point for RPA is the ability to work with legacy IT infrastructure and software that many insurance companies may be using. After all, the bots utilize the existing software and in many cases are mimicking human interaction with the systems, so there are no urgent needs to invest in upgrades. So while it is great to be able to extend the lifespan of legacy infrastructure, it shouldn't be seen as a reason not to modernize a company’s systems indefinitely if they want to remain competitive in the future.
When implemented in its most basic form, RPA frees employees to work more efficiently and focus on the work that makes the best use of their skills, rather than on time consuming tasks like data entry. However, the technology offers even more exciting possibilities to the insurance industry when combined with AI to deliver more intelligent end-to-end process automation in a way that can significantly reduce operating costs, all while improving the customer experience.