4 tips for implementing automation in insurance
Competitive pressures are mounting for all lines of insurance business, leading to an imperative to implement more intelligent automation processes across the value chain.
That’s according to a recent KPMG report, “The Automated Insurer: Next steps on the journey to intelligent automation,” authored by principals Gary Plotkin and Michael Adler along with director Prateek Saxena.
Intelligent automation is defined by the firm as combining several automation technologies – robotic process automation, machine learning and cognitive computing – into an ecosystem that allows carriers to streamline and optimize current processes to better meet customers’ needs and free up skilled staff to work on more valuable work. While most carriers are already aware of the technology’s benefits, the vast majority – 86%, according to a recent survey of CEOs by KPMG – are only testing it.
The consultancy suggests four steps insurers can take to prepare their enterprises to fully leverage the benefits of intelligent automation:
- Start small, but think big. While it’s easy, and somewhat satisfying, to stand up a small project quickly, the cost and efficiently benefits won’t come from piecemeal efforts, KPMG writes. Insurers should start any automation project with scale in mind, and how to get successful deployments into more areas of the company faster.
- Determine the size and scale. Once the decision is made to always have scale in mind when evaluating a program, the next step is to define what scale looks like. KPMG recommends insurers start right from the minimum-viable product with a look at what small-scale implementations can be done quickly, and then what higher-level areas they want to tackle.
- Determine the operating model. Preventing duplicative work is key as that saps efficiency from the project. Rather than have each line of business creating its own processes, vendors, technologies and timelines, KPMG says carriers have found success with a center of excellence, hub-and-spoke or program governance models that centralize most decisions.
- Assess longer-term impacts to people and process. Any implementation of automation is going to impact how jobs across the enterprise work. Implementation teams need to be focused on how end users’ day-to-day duties will be impacted by the new technology, get buy-in early and move the entire organization toward a digital first mindset.