What Do You Drive?

We hear people in marketing say, “Content is king.” Maybe. It depends on the context. That’s why we think context is king. That thought was reinforced when we wondered if modern, computerized cars could or should be compared to modern, computerized policy administration systems. The answer is, “It depends.” And it depends on context. Here’s what we mean:

Cars, like life, are about tradeoffs. Older cars have basic mechanical systems. They can be easier and less expensive to repair. Depending on year, make, and model, parts are available and inexpensive. They don’t include features that are tied to subscriptions like OnStar, drive recorders, infotainment systems, navigation updates, and others. And they’re less susceptible to technological failures like software glitches, sensor failures, or hacking.

On the other hand, more modern cars have advanced safety features like automatic emergency braking, lane-keeping assist, blind-spot monitoring, adaptive cruise control, and better structural resistance to crashes to improve safety. They’re more fuel efficient. Their computer systems optimize engine performance, transmission shifts, and handling. Touchscreens, smartphone integration, adaptive cruise control, and heated seats and steering wheels enhance the driving experience.

In context then, if you prefer lower upfront costs, if you enjoy doing some of your own repairs, you don’t need modern technology, and you accept lower safety and efficiency standards, you’ll prefer an older car. But if you value safety, fuel efficiency, comfort, and modern features, and are willing to pay for higher initial costs and potentially higher service and repair costs, you’ll prefer a newer car.

Back to the Future

Policy administration systems, also like life, are about tradeoffs. Older methods that were manual and paper-based permitted personalized underwriting decisions and the judgment of experienced adjusters for claims adjudication. With no reliance on technology infrastructure, there were no system outages or software bugs. Those methods were slower, more labor-intensive, prone to errors and delays, lacked scalability, yielded few data insights, required costly storage, and tough to retrieve and audit.

But we don’t have to go back that far. The advent of modern policy administration dates back just 25 years to Y2K. Since then, in short, mainframes have been replaced by early digitalization and automation efforts. Those efforts started bringing down silos and incorporating flexibility, configurability, and customization with diminishing levels of IT intervention. Service-oriented architecture (SOA) enabled integration with other systems and data sources. User interfaces shifted from desktops to web based. Risk assessment and pricing started to incorporate data analytics. The emergence of SaaS models reduced infrastructure costs, improved scalability, and enabled faster updates. Digital portals enabled self-service. Mobile apps became standard. And AI and machine learning found their way into everything from risk assessment to underwriting, from claims automation to individualized pricing.

But everything still comes down to context and preferences. Older methods are outdated in most situations but retain value in specific, low-tech contexts. They may still work for small, specialized insurers or unique risks requiring human judgment. Newer systems provide efficiency, speed, scalability, and data-driven insights that help insurers meet competitive market demands and customer expectations.

Once again, like life, cars and policy administration systems are about choices. And choices depend on context.

What do you (choose to) drive?