As technology continues to advance, the insurance industry is seeing a shift toward automated underwriting approval processes. This trend has been gaining momentum over the past few years and is expected to grow as insurers seek to streamline their operations and reduce costs without losing the human touch.

When you have a problem with speed in a business process, but you don’t know exactly where the slowdown is happening, frustration builds for both teams and leaders. And it’s a widespread issue for enterprises trying to accelerate their pace and increase their capacity for work in the pursuit of digital transformation goals like improved customer onboarding or faster time to market.

With record-high inflation, climate change, and an economic downturn on the horizon, the insurance industry is in a pressure cooker of unpredictable change. Sometimes this change happens over time. Sometimes it seems to happen all at once. To come out on top, insurance companies need new workflow and operations strategies that leverage process automation to streamline processes, reduce errors, and improve the customer experience.

Leading insurers are prioritizing claims process automation. Why? Because expenses related to preparing, processing, paying, and adjusting claims represent the most significant share of an insurer's operating costs. Even more than that, 87% of policyholders say the claims experience directly impacts their decision to stay with an insurance provider. But for many insurers, complex workflows, siloed data, and disparate systems have turned the claims process into a painful customer experience.

If you asked anyone at your organization, there’s no question they could name at least one business process that needs streamlining—probably they could name several. That’s the hard truth for leaders looking to gain digital transformation speed in pursuit of critical business goals, like faster customer onboarding and faster time to market.

The pain points that drive IT and business leaders to implement process automation are clear: broken or slow business processes, automation wins that don’t scale, and data silos. All three create problems that can stop critical digital transformation work from reaching its goals. These problems not only cost time and money but also open companies up to risk and compliance trouble and employee engagement woes.

Businesses today know that operational efficiency, effectiveness, and productivity are keys to competitive advantage. And process automation tools are being adopted more and more because they help IT and business leaders turn those goals into reality. If you’ve spent time researching ways to boost efficiency by taking advantage of automation opportunities, you’ve likely come across the related terms hyperautomation (which is synonymous with process automation) and intelligent automation.

Business process automation (BPA) refers to the use of computer systems and software to automate business processes or tasks. These days, many people simply refer to BPA as process automation: a set of tools that automates entire business processes, end to end. Robotic process automation (RPA), on the other hand, is a single part of a process automation toolset. RPA fits into a process automation strategy by automating repetitive tasks within a process.

Have you seen the efficiency gains you’d hoped for from your investments in task automation tools like robotic process automation (RPA)? Despite prioritizing automation efforts, many IT leaders still lack the tools for broader, end-to-end process automation—or as Gartner calls it, hyperautomation. If you’ve found yourself grappling with numerous disconnected islands of automation, where do you go from here?

Are you confused about the multiple types of business process automation? You’re not alone. Automation tool vendors seem to have created more flavors than a contestant on Top Chef. Let’s get to the bottom of the differences between the various types of process automation and find out what they can and can’t do, in plain terms. Here’s a starting hint: Get ready for synonyms. In some cases, different analyst firms and tool vendors use different terms for the same ideas.