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Four Operational Challenges In The Insurance Industry And How To Solve Them Using RPA

Forbes Communications Council

Founder & CEO at Stealth Scaling.

Insurance is a massive industry, and in 2023, the key focus for virtually every company is increasing profitability and increasing operational efficiencies. As the founder and CEO of a company that offers an intelligent automation platform with humans in the loop, I've found that the insurance space has several operational challenges to overcome regarding data.

1. Data Being Inaccessible

Believe it or not, the insurance industry still leverages a lot of PDFs that require digitization, and a lot of the data can get lost due to manual, repetitive work.

2. Expensive Manual Data Entry

The cost of labor can make it too expensive to hire full-time employees to process data manually.

3. Automating Workflows Without Humans In The Loop

There are a lot of insurance processes, such as claims, collections, pricing and client documentation, that can be automated but often need a human to review the bot's work.

4. The Expense Of Automation Tools

RPA and automation seem to be gaining traction in the insurance industry, but between buying licenses, setting up a center of excellence (CoE) and hiring the labor to maintain the CoE, it can become a challenge.

So with these four operational challenges in the insurance industry in mind, the question becomes: How do we solve them?

1. Finding An RPA-As-A-Service Provider That Offers Human Support

As I mentioned earlier, implementing RPA can be very expensive because you don't just have to pay for software licenses, you also have to invest in the on-going maintenance and support of these automations.

On top of that, your team still has to be "in the loop" to handle exceptions that the bot can't handle, so as an executive, you still have to staff full-time employees to be involved in these processes.

One recommendation would be to find an RPA-as-a-service provider who can provide the licenses and implementation support and handle the ongoing maintenance of the automation.

Consider looking for a provider who can provide humans in the loop to handle any exception or act as a backstop so you can completely automate processes end to end and lower your labor costs.

To choose the right provider, start first by asking what tasks require the most people or full-time employees to complete. That is how to first prioritize which process you would like to automate. Then, determine if that process really requires any logic or if it is rule-based and high-volume. These questions will help you determine which providers to look at based on the answers. Ask providers if you need to buy licenses and how much they cost annually. How much would implementation and ongoing maintenance cost? Measure what the all-in cost per transaction will cost you prior to automation and after automating the process. Some companies charge for licenses but require you to build out the automations yourself. This is expensive because then you either have to hire a partner or do it yourself by hiring RPA developers, solutions architects and so on. My recommendation would be to look at RPA-as-a-service companies who don't charge much or anything for implementation or ongoing maintenance. They might only charge per transaction or charge a small monthly subscription fee.

2. Focusing On Automating Processes That Will Provide The Biggest ROI

RPA alone is not a quick fix. You need to make sure that you optimize your processes for a frictionless customer experience. You also want to focus on automating the processes that will drive the most outcomes and provide you with the biggest ROI.

In the insurance industry, I've found that the best processes to focus on are typically the claims and collections processes and anything that involves data extraction.

An easy way to determine which process will deliver the biggest ROI is to think about what processes have the highest transaction volume and are rules-based that don't require a lot of creative thinking.

The first thing you should do to determine what processes are taking up your staff's time is to do what is called process discovery. You can use tools like Celonis or UiPath Task Capture to track how much time your staff is spending on particular tasks and how they're doing them.

Another thing you can do is look at how many full-time employees you have that are doing a specific task, calculate how many transactions they are generating per month, and determine how much you are paying them. Then you can calculate what your internal cost per transaction is. Automating the processes with the highest cost per transaction can provide you with the highest ROI.

Here is an example of a starter bot for the insurance space that companies might use for the intake and triage process.

• Step 1: The bot monitors emails and extracts data from documents in incoming emails.

• Step 2: The bot aggregates data from the policy and creates a claims case.

• Step 3. The bot assigns the claims to the appropriate processor or adjuster based on product, type, amount and so on.

• Step 4: The bot sends an email to the adjuster or manager.

• Step 5: The human-in-the-loop handles any exception the bot can't handle as a foolproof backstop.

In conclusion, insurance companies can save money by leveraging intelligent automation, but they should focus on automating the right processes and finding a partner who can help them lower costs on licenses, implementation and ongoing maintenance in order to do so.

It's best to start with a very easy process to automate to gain a quick win. This could be automating your invoices or doing data reconciliation. From there, you can take on more and more complex automations over time.

Change management is also important when you begin automating processes. You should communicate with your team openly and honestly about what you're planning on automating and assure them that a lot of the staff will be upskilled and freed up to focus on higher-value work. That way, staff isn't nervous about losing their jobs.


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