- Intelligent Process Automation alleviates the necessity of humans to perform repetitive tasks while eliminating errors and bottlenecks.
- Robotic processes combined with artificial intelligence and machine learning result in efficiency, enhanced security, and better customer experiences, translating to customer loyalty and a better bottom line.
- OZ consultants have the expertise to help your insurance team identify what processes are ideal to automate and take you through the steps.
These days, insurers are facing the pressure of doing more at a fast pace, and customers have high expectations. The insurance industry, while strong on experience, has been bogged down by reliance on manual work, outdated materials, and legacy systems that make it almost impossible to keep up with standards set by today’s customer—that is, unless it adopts a different process model—that of intelligent automation.
The good news is that with the increased adoption of digital tools and technologies among agents and brokers, there is also increased use of self-service digital channels. Companies appear to be ready to embrace process automation, and when they do, there are benefits to customers and employees in speed, efficiency, higher data accuracy, and more. In fact, a 2020 survey reveals that 89% of insurance executives are rapidly shifting to digitization.
Automation can lower workforce costs dramatically in a relatively short period of time. The return on investment (ROI) for intelligent process automation hinges on dedicating staff to higher priorities, reducing human error, and enhancing customer satisfaction.
While the financial services industry embraced process automation years ago, the insurance industry has been slower to adopt this technology. However, many insurance companies have begun pilot automation programs that include Robotic Process Automation (RPA) and Intelligent Automation (IA) in the past year or so. The RPA market is growing at breakneck speed. Grand View Research put the market value at USD 1.57 billion in 2020, and it is expected to grow at a CAGR of 32.8 percent from 2021 to 2028.
The 3 Components of Intelligent Process Automation
Intelligent Automation (IA) has three cognitive technologies:
- Artificial Intelligence (AI) and Machine Learning (ML): This is the decision engine.
- Business Process Management (BPM): This automates workflow.
- Robotic Process Automation (RPA): Software bots are used to complete back-office tasks (i.e., data extraction, filling out forms, repetitive data entry).
What type of processes are best suited for RPA?
RPA can be installed quickly, does not require changes to existing systems, and is comparatively inexpensive.
Typically, the first processes to be selected for RPA are those that are highly repetitive, prone to errors, and take your employee’s time away from more important things. When deciding which processes to automate, here are some questions to ask yourself:
Is the process rules-based?
Does the process consist of clearly defined steps that are not open for interpretation? Or, does the process have rules with a lot of exceptions? A process with many exceptions is a good candidate for an RPA system with a Machine Learning component to understand how to manage those situations over time.
Is the process labor-intensive?
Tasks that are primarily administrative and divert a worker’s time away from their primary job are excellent choices for automation. These types of processes are easily measured based on freed-up hours, and depending on the tasks chosen, multiple FTEs can be freed up to focus on more value-based activities.
Does the process have readable inputs?
RPA requires readable inputs—text-based data, user activities (keyboard strokes and mouse clicks), Optical character recognition-fed data (OCR), and green screen. For instance: processes that require an employee to scan emails, documents, spreadsheets, PDFs, or even images to then enter information into a digital system are prime candidates for RPA.
Non-OCR processed images or non-digital formants are unreadable with RPA.
Is the data structured?
RPA works most easily with data that is distinctly defined and searchable, called structured data. Some examples are names, addresses, credit card numbers, geolocation, etc. Unstructured data is everything that is not easily searchable, like audio, video, and free-form writing formats. RPA can be used with some unstructured data inputs but will take longer to implement and see a strong return.
Measuring RPA ROI
Before executing a process automation strategy, you may want to calculate the net gain you will see from transitioning. Divide this by the net investment needed to transition (i.e., the tools and resources you use), and you will get your ROI for automated testing. (OZ has an ROI calculator for your RPA project, contact us for more information).
Start with running a pilot program, and then build on that success.
Once you implement RPA, your ROI could be measured in weeks or months—NOT in years. A typical payback time is three to nine months.
The Bottom Line
As with any business tool, the choice to intelligently automate processes in your insurance company can bring a powerful return on your investment of time and money. Efficient, fast, and error-free service translates to customer loyalty, which is essential to the health of your organization. A well-planned IA approach will help you achieve these goals!
OZ is a consulting and technology solutions leader that helps companies accelerate business processes and provide access to real information to drive real insights. Start the discussion today. One of our consultants can help you move forward.
1 Grand View Research: Robotic Process Automation Market Size, Share & Trends Analysis Report https://www.grandviewresearch.com/industry-analysis/robotic-process-automation-rpa-market