Pressure on insurers is mounting on multiple fronts. New technologies and evolving customer expectations are driving ever-faster change. Regulatory requirements are intensifying. And customers are seeking greater choice, more flexibility and easier omni-channel interactions. How well does your organization use intelligent automation (IA) to deliver tangible benefits?
Legacy technology platforms and time-consuming manual, paper-based processes are two obstacles to progress. At the same time, digital challengers are encroaching on traditional lines of business, while technology giants and emerging players make further inroads into financial services. Against this background, IA presents an opportunity to move beyond cost savings to radically improve the insurance value chain by using a combination of solutions such as robotic process automation (RPA), machine learning and cognitive technologies. And to streamline and optimize processes to improve the customer experience and enable employees to focus on added value tasks.
While IA can offer a financial return on investment, it can generate value across business functions:
We organize businesses’ IA maturity into five levels. In our experience, most insurers are at Level 2 – incremental – with implementations generally limited or in the planning phase. Crucially, we see how insurers are likely to get stuck at this level if they view IA only through a cost savings lens.
The key is to step back and take a wider view.
Create an IA vision for the organization: Ask questions such as how you can best use IA tools and technology to support your business goals and strategy. Having a clear vision helps prioritize specific opportunities for automation such as for example in claims and underwriting.
Maintain a broader focus: Many insurers focus on automating existing processes and applications. It’s important to look past this to how IA could help you be more proactive by analyzing customer data and predicting future trends. Overall, to improve your customers’ experiences, achieve better data governance, enhance employee satisfaction, and reduce the risk of errors.
Optimize before moving forward: Ensure your organization is getting the most out of your existing systems prior to introducing automated process support, to avoid inherent inefficiencies being recreated and repeated even when using new technology.
Start small but think big. Plan early deployments strategically, with scale in mind. For example, identify a few repetitive tasks or a single process that can be scaled up later to achieve more tangible benefits. This helps to gain and maintain stakeholder buy-in and confidence, as it shows a proven return on investment or achievement of other measurable benefits.
The second step is to determine the size and scale of the IA program – the desired end state. This provides a target to work towards. It could involve starting with a tactical approach to lower-value use cases, with progress towards a more holistic approach over time.
Finally, determine the operating model to ensure you have the necessary structures in place for your IA strategy to succeed. This should be organization wide, because if individual functions and departments each produce their own plans this will result in duplication of effort and extreme difficulty when integrating and aligning approaches down the road.
Through all of these considerations, insurance CEOs should recognize that IA is transformational. It is critical to think about the journey to IA as an end-to-end business transformation that will impact business model, operating model and ecosystem.
Publication: The Automated Insurer