"Hello, Mr Kaiser!"

Remember him? At least our dear German readers will: From the 1970s to the early 2000s he came to our living room before every newsreel. As the insurance representative of the nation, he embodied trust, closeness and fairness. Whether property, casualty or motor vehicle insurance, Günther Kaiser knew what was going on. He was the most famous advertising face in Germany. Thanks to the large comparison portals, he is now retired. 

The urgency to adapt

And this has a significant impact on the business of composite insurers. As the Boston Consulting Group states in its report on the growing importance of pricing, “insurers must effectively adapt to new technological, market, and consumer complexities with better, more dynamic pricing if they want to maintain competitive advantage in the insurance industry.”

Today's digital economy provides for considerable market transparency, and the increasing presence of online insurance aggregators drives the market into a permanent price comparison. This makes it necessary to be able to react quickly and adapt to one's own tariffs. Technology disruptors, external data providers and the Internet of Things, as well as wearables and telematics services, also give insurance companies the opportunity to develop new innovative pricing models. This includes dynamic pricing, better risk assessment, and the right discount depending on willingness to pay, willingness to buy or probability of migration. And finally: More sophisticated consumers are now open to new value propositions based on new variables (individual mobility patterns, limited and individually adjustable coverage) and requiring dynamic price structures.

The quest for pricing accuracy and speed

What does this mean for insurers? Here are a few quotes from leading actuaries and persons in charge that I have often heard in this and similar forums in recent months: 

• "We need to adapt to the market faster – it takes four months to deploy the tariff.”
• "We need to stay relevant and competitive, so we need more insightful pricing models."
• "We must improve the profit from the current policy portfolio by allocating the optimum price to our customers.”
• "We must protect our customer base."

In other words, insurers need new pricing skills to improve the accuracy of technical pricing. They want better optimisation techniques for premium adjustments in order to achieve the maximum profit from existing portfolios. And they need real-time pricing capabilities to implement underwriting engines for agile tariff deployment.

It could be simulated

To be competitive in this changing market, the rate-making process needs to evolve, and a mix of new skills needs to be added:

• Faster development of tariff models through an agile methodology, including machine learning techniques.
• Faster delivery of tariffs in production with the option to embed complex price optimisation models in real time, along with a model governance solution.
• Optimisation of renewal pricing, 
• Access to powerful simulation capabilities.

Is this all just theory? Absolutely not, as the example of the Spanish insurance company Caser Seguros shows. Caser Seguros offers a wide range of products for home, car, health, life, etc. Its most important challenge was the impact on sales and earnings from slow pricing and underwriting processes. And, of course, despite price wars between insurance companies and an economic downturn, it was important to win and retain customers. With the help of SAS, the insurer succeeded in improving customer loyalty by 50 percent in important customer segments despite the economic situation. Portfolio premiums were improved by optimising premium adjustments and the underwriting process. Caser Seguros can analyse market trends, evaluate competitors' prices and products, and make pricing and underwriting decisions in real time. All in all, this means faster adaptation to market conditions.

What if?

Now that Mr Kaiser is retired, the focus is on competitive tariffs, optimised portfolios and real-time pricing. What if insurance companies could fully exploit the potential of modern machine learning algorithms and increase maturity levels with standard software? With better methods, more accurate risk assessment and "sharper" tariffs can be achieved, which would increase margins. What if actuaries could provide robust, efficient and repeatable processes using a standardised and unified platform? They could significantly increase their throughput and make better use of their resources. And what if insurance companies could use a flexible real-time engine to quickly deliver rates that give actuaries more control? They would be more agile and could update tariffs daily on the market. And that's what we should talk about!

What if insurance companies could use a flexible real-time engine to quickly deliver rates that give actuaries more control? They would be more agile and could update tariffs daily on the market Click To Tweet.

Mr Kaiser, you have earned your retirement!