Why RPA and AI Are Game Changers for the Insurance Industry

• Robotic process automation (RPA) and artificial intelligence (AI) are both valuable and have their place in today’s insurance company
• Realize the competitive advantages of automating processes with RPA and AI beyond cost savings
• Create a digital strategy adoption plan
• Realize the benefits of adopting these different automations in your digital strategy

While both Robotic process automation (RPA) and artificial intelligence (AI) can be used to automate different types of processes, they do so differently. AI automation is based on using deep algorithms to calculate and analyze data in ways humans can’t, while RPA is more about taking smaller repetitive business tasks off the plates of your workers. Here’s what you need to know to leverage both in your insurance company’s digital strategy.

Let’s start with an analogy to illustrate the differences in these types of automation: Say you agreed to run in a 10K race without adequately training for it. On race day, it is exceptionally hot. Halfway into the race, you want to quit.

In this case, either method of automation — RPA or AI — would help your situation.

Getting to the finish line more easily could be automated by hopping on a motorized bicycle. Getting to the finish line faster could be automated by using Google Maps’ automated intelligence and traveling the shortest distance instead of the prescribed race route. Either automation might be helpful if all you really want to do is get to the finish line. Adopting both by riding the motorized bike and traveling the smartest route would be transformational.

It’s the same with using RPA and AI at your insurance company. To clarify, let’s look at each automation individually and take another pass to see what they might lead to when used together for a modern insurance company.

Day to day, insurance customers and agents rely on your platform’s ability to perform the same tasks the same way, time and again, to get the job done. An insurance company that has been in business for years has these processes perfected. In fact, you are probably already using RPA in some areas to automate processes but may not be calling it that.

Your customers enjoy faster and more error-free service when you adopt RPA. Your workers will be glad RPA takes some of the more tedious processes off their plates.

Definition: Robotic process automation (RPA) refers to software that can be easily programmed to do basic, repetitive tasks across applications. What RPA is not is a completely automated system — RPA still relies on humans to program the bots, give them tasks, and manage them.

Examples: Look around the insurance industry today and you will see many examples of RPA. Insurance companies use it to extract data, verify claims, and process invoices. On the horizon, expect to see RPAaaS (RPA as a service) that provides RPA services on-demand from the cloud. When combining RPA with SaaS, you get even more benefits like ease of use, automatic updates, and scalability.

Adoption and ROI: The key to adoption of RPA across the company is good process definition. Procedures typically develop from different internal systems. A very good understanding of this must be established in order for RPA to be successful. An often-cited ROI stat is to expect 30% to 200% ROI in year one. Even so, don’t just look to cost and time savings, measure employee satisfaction as well. Wondering where to start? Try our simple RPA checklist.

Artificial Intelligence, on the other hand, is a relatively new technology. There are things that could be automated but still require some decision-making, which makes them a poor fit for RPA. For some of these, we can apply AI. Again, your customers may notice an enhanced experience and your employees will be happy to have the intelligence that AI brings to bear simplifying their duties.

Definition: While RPA is a software robot that mimics human actions, AI is the simulation of human intelligence by machines. AI is mainly used to calculate and analyze data with deep algorithms.

Examples: Insurance companies were some of the first businesses to collect data in mainframe computers. Fast forward to today, and AI is being deployed in numerous ways across the insurance industry. One of the most recognizable automations is using the chatbot to aid in customer service. Other examples are using AI in claims processing, underwriting, and fraud detection.

Let’s look more closely at how some insurance companies are using AI to handle fraudulent claims. The data for this labor-intensive task was too varied to be suitable for typical RPA. As a result, insurance companies are using AI to make sense of irregular data sets. From there, the business can develop new algorithmic models that flag potentially fraudulent claims data with less work, which leads to faster service and better control than before.

On the horizon, expect to see insurance companies increasing their agility and insight through the combination of Big Data and AI analytics. These insights will affect every aspect of operations and provide new opportunities to deliver exceptional customer service.

Adoption and ROI: The key to adoption is having good data to train the algorithm. This does not happen overnight. As a result, ROI and timelines vary from one AI project to the next and from company to company.

It’s easy to see that both automations are valuable and address different needs. Insurance Automation 2.0 is the term we use when we talk about combining the power of RPA and AI for future automations, like natural language processing, recommendation services, and online customer support. It’s not hard to imagine how all of these could be used to create the insurance company of the future.

Some insurers will gradually automate one process and then another. Others will choose a digital platform to sync up all of their technology at once. The point is to have a well-designed digital strategy. Many times these automation adoptions exist on a tech continuum that begins with RPA and moves into AI.

The goal is excellency centered around the creation of a process center and a data center. At that point, you have truly earned the moniker, “Digital Insurance Agency.” You don’t have to be the first among your competitors to reach these goals, but you don’t want to be slow to move due to the inherent advantages.

With the advantages readily available today, it’s not a matter of if but when you want to adopt them.

For example, data analytics rely on data. You must start collecting and making this data usable today in order to mine it tomorrow. There are first-mover competitive advantages to automating processes with AI beyond cost savings. The insurance companies already adopting AI will have the insights for better decision-making first.

A good starting point is to meet with a software consultant to create a digital strategy for your insurance company. With a plan underway, you will soon be enjoying the benefits of automation, such as the ability to:

• Meet modern customer expectations
• Increase operational effectiveness
• Enhance risk management
• Reduce costs of manual processes
• Increase agility and insights

Moreover, as these solutions are implemented, 80% of insurance companies see an increase in profits once the solutions are fully implemented.

When you are ready to line up your custom automation system, RD Global can help with planning and developing the software solutions and digital platforms you need to make it happen. Our consultants work daily with clients to make sure the launch is easy, not disruptive to their business, and that they receive maximum benefit from these high-impact tech solutions. Contact RD Global today to get started.