1. Core systems that have evolved over decades

Most insurers have core systems that have been continuously expanded over many years—in some cases, over decades. New products were added, regulatory requirements were implemented, custom processes were developed, and numerous interfaces were created. These systems still fulfill their purpose. At the same time, they make change difficult.

The more closely business logic, product rules, and custom developments are intertwined, the more complex each adjustment becomes. A small business-related change can quickly turn into a project involving multiple applications, various departments, and extensive testing.

The real problem here is not the age of a system, but rather its ability to evolve.

2. Digitalization Often Stops at System Boundaries

Insurers today are investing in customer portals, broker portals, mobile applications, and AI solutions. However, these innovations only deliver their full value when they are seamlessly connected to core insurance processes. Without standardized interfaces, custom integrations are required.

Each new application thus increases the complexity of the entire IT landscape. The result: It is not the development of new digital services that becomes the bottleneck, but rather their integration.

3. Speed Becomes a Competitive Factor

A few years ago, it was acceptable for the launch of a new insurance product to take several months. Today, the market is changing much faster.

New distribution partners, embedded insurance models, regulatory changes, and AI applications all demand shorter development and release cycles. Many insurers are therefore finding that it’s not a lack of ideas—but rather the technical ability to implement them in a timely manner. As a result, innovation is increasingly determined by architecture.

4. Data Is Available—But Rarely Consistent

Insurers have enormous amounts of data. Customer information, policy data, claims histories, and documents are often already available in full. Nevertheless, this information is frequently scattered across different applications. Duplicate data storage complicates automation, analysis, and the use of artificial intelligence.

This is because AI does not require as much data as possible; it requires consistent, high-quality data.

5. Artificial intelligence doesn’t just change individual processes

Hardly any other topic is currently occupying the industry more than AI. Discussions often focus on individual use cases:

• Automated correspondence
• Document analysis
• Claims processing
• Chatbots
• CRM
• Claims management
• Portals
• AI

The real challenge, however, lies elsewhere. AI is changing expectations for the entire IT architecture. When information is scattered across numerous systems or business processes cannot be digitally mapped, even the best AI quickly reaches its limits.

The foundation of successful AI projects is therefore not the model alone, but rather a modern and integrated platform.

6. The challenge does not lie in introducing new software

Many digital transformation programs begin with the search for a new solution.

In doing so, they often overlook the fact that the real added value comes from the interaction of all systems.

The question is therefore not:

“What software are we missing?”

But rather:

How do we create an architecture in which all systems work together efficiently?

Conclusion

The technological challenges facing the insurance industry have changed.

In the past, the focus was often on introducing new software.

Today, the focus is on further developing existing systems so that they can provide long-term support for innovations, regulatory requirements, and new business models.

The most successful insurers will therefore not be those that adopt as many new technologies as possible.

Rather, they will be those whose IT architecture enables change rather than hindering it.