Everyone seems to be on board the innovation train. But when it comes to the insurance industry, despite many insurtechs entering the market and countless innovation conferences heralding a new age, the reality is that there is very little material change other than what we see from neo-insurers.
Credit where credit is due - the industry is ready for change, but it is hard to do. There are many hearts and minds to win when it comes to adjusting the insurance value chain. Bookended by shareholders and customers, but in between there is a complex matrix of reinsurers, regulators, brokers, administrators, and distributors. A decision to change may require many approvals and can be polarising in an industry accustomed to avoiding risk. Change always carries some level of risk. So does inertia.
Why does legacy technology still hold insurers back?
The fact that established insurers have been around for decades means they implemented technologies when the landscape looked entirely different. Housing policy data and the processes that regulate how policies change over time is not straightforward - in some cases those policies exist for decades. Failed transformation and migration projects are well documented, so it is understandable that some insurers guard their legacy systems carefully.
That old legacy excuse is wearing thin though. The technology industry has evolved sufficiently to offer practical ways to navigate this. The challenge that remains is legacy thinking, not legacy technology. Shifting culture is hard in an established industry, but as some have already demonstrated, it is not impossible.
Why do innovation roadmaps often disappoint?
The rate of change in technology is accelerating. Why then are we surprised when a three or five year transformation roadmap ends up feeling like an anticlimax? While you were busy delivering that roadmap, needs and desires changed - and quite likely the people who sold the dream in the first place.
Agility is the cornerstone of innovation. While major projects like replacing a policy administration system can take a long time, if an organisation is planning to deliver today's innovation in three years, then we should not be surprised when the destination has moved by the time we arrive.
Dream big, plan small, test regularly. If you are not convinced, look at what neo-insurers are doing.
How should insurers think about timing and readiness?
New solutions enter the market regularly, offering genuine alternatives to how we might approach insurance from acquisition through to claims. However, while some may earn their way to pilot, few make it into production - which can chip away at an organisation's confidence in their ability to innovate at all.
You cannot fly to the moon without a spaceship. As much as we may want the next innovation, we are tethered to a reality that requires identifying the natural order of a transformation - which often means getting the foundations right first.
Take AI. The conversation started a long time ago and is only now reaching maturity, but many organisations still have technical and operational constraints that undermine their ability to properly use it. The Decision Pyramid framework addresses this directly - AI compresses the effort layer, but the decision layer needs to be built on explicit, auditable business rules before AI can be trusted in production.
What role does commercial thinking play in innovation?
It continually surprises us how rarely innovation is measured with a commercial lens. Innovation costs money and the bigger the organisation, the more it will cost. Failing to validate the impact innovations are expected to deliver can burn cash and divert resources, undermine confidence and the innovation culture, and complicate the technology ecosystem in ways that bring hidden future costs.
The opportunity to be more commercial does not just sit at the executive table. It can be instilled in the culture of the technology team, particularly at the analysis and design end of projects, where decisions about requirements and design have an exponential effect on cost and value downstream.
For an introduction to how process automation works, read What is process automation?
Frequently asked questions
Insurance involves a complex matrix of stakeholders - reinsurers, regulators, brokers, administrators - and decisions to change require multiple approvals. Legacy systems and risk-averse culture compound the challenge. The barrier is often cultural as much as technical.
Start small. Identify high-value processes where automation or rules externalisation can deliver measurable improvement quickly. Build confidence and demonstrate value before scaling. Three-year roadmaps rarely survive contact with reality.
Look for processes that are high volume, clearly defined, and currently manual or semi-manual - claims intake, underwriting pre-checks, policy renewals, and compliance reporting are common starting points. Read our top 7 insurance automation use cases for specific examples.