Pricing engine implementation for modern insurance pricing

Apr 30, 2025 Core Systems, Data Advisory, Pricing

Insurance Pricing on the Edge

Insurance companies have long operated in stable economic conditions and learnt how to deal with pricing cycles that occur due to monetary impacts, sometimes in combination with large loss events. They could rely on basically stable statistics. The companies that could use the most precise and appropriate statistics were able to offer the best pricing. But this has changed. The recurrence of inflation and the elevated exposure to natural catastrophes force insurance companies to change their approach to pricing. The growing influence of price comparison websites contributes to the acceleration of change in insurance markets. This has been demonstrated by the rollercoaster-like developments in motor insurance in the UK. After price increases of more than 40% in 2024 the market currently witnesses a steep decline. Price comparison websites demand high technological capabilities of insurers, low delays and ultra-high adaptability.

Avoid onerous IT administration

We see insurers in many markets struggling to cope with the new challenges of pricing, facing problems in deployment time for new pricing models and slow adaptation to market changes. Both problems may lead to serious consequences. Deployment of new rating models should be quick and easy, driven by the pricing team and not hampered by burdensome IT administration. 60–70% of insurers are still using Excel for pricing-related tasks. Excel is a good solution and can be helpful in data analysis, but the insurance business should not rely on it for the entire pricing process.

In Excel…

you cannot cover the whole pricing process
you cannot run portfolio simulations with sufficient accuracy
you cannot test efficiently

Similarly, the support provided by Policy Administration Systems (PAS) in pricing is not sufficient.

In core system technology…

you cannot deploy quickly and easily
you cannot deploy advanced pricing strategies
you cannot have live pricing strategy validation

Pricing engines can help insurers quickly and effectively deal with new risks while eliminating the potential consequences of inefficient pricing. In several pricing engine implementations, we see the benefits of pricing engines. Better and faster implementation times, fewer pricing errors, a single source of truth, and reduced reaction time to market changes are the most outstanding examples in a long list of advantages. According to GIRO 2022, more than 150 industry experts have estimated that adopting a pricing engine and its features can lead to a 2.8% reduction in loss ratios. At the beginning of our discussions about pricing engine implementation, we often observe an attachment to legacy solutions such as Excel. How can these objections be overcome?

Six months for implementing a new rating model?

It is difficult to maintain a stable pricing process when relying on Excel and similar tools. In such an environment, the process is distributed across multiple systems and teams, making it easy for employees to lose track of changes because they cannot rely on a single source of truth.

A simple and fast implementation process allows insurers to realise benefits quickly. We have seen insurers wait up to six months to implement rate changes because they first needed to contact their Policy Administration System (PAS) vendors.

With pricing engines in place, actuaries can focus on their core expertise. They possess broad analytical and technical skills, which insurers should use effectively instead of requiring them to create time-consuming portfolio simulation macros that are difficult to maintain.

Data is the foundation of the rating and pricing process. All quotes—whether or not they result in the purchase or renewal of a policy—should be stored for further analysis by actuaries. A pricing engine ensures that all quotation data is recorded and stored in the right place.

When selecting a pricing solution, an insurer should consider the following:

Model management: Oversight mechanisms should meet the expectations of both management and regulators. Professionals responsible for creating, refining and implementing models also need immediate access to previous versions of their work and to other models containing relevant components or techniques. Therefore, version control is an important pricing engine capability.
Model import: Actuaries may develop initial models outside the pricing engine. A solution that can seamlessly import and run external models with little or no customisation can provide significant efficiency and value.
Integration and compatibility: Smooth integration between the pricing engine and the policy administration system is essential. In many cases, the key reason for implementing a new pricing engine is an unstable existing integration that causes performance issues and may lead to the loss of potential customers who wait too long for a quote.
Reporting and audit: Comprehensive reporting helps ensure that pricing decisions are transparent and can be justified during audits. Automated reporting and audit processes within the pricing engine can save insurers considerable time and reduce operational risk.
AI capabilities: In recent years, we have seen more AI capabilities being introduced into pricing engines. AI can support modelling and pricing teams, helping insurers achieve their business objectives.

Negative impacts of under- and overpricing

Sollers provides end-to-end pricing engine implementation support. We help insurers prepare both the solution and the new organisational structure while managing PAS integration, testing and data management. Through our advisory services, we also support the transformation of the insurer’s business and IT architecture.

Insurers that postpone pricing changes may face the consequences of ineffective pricing, which generally fall into two categories: underpricing and overpricing. Underpricing has a direct negative financial impact, as claims payouts and operating costs exceed revenue, potentially threatening an insurer’s financial stability. Overpricing, on the other hand, limits growth and weakens overall competitiveness. It can also seriously damage the insurer’s reputation.

Overpriced insurance coverage regularly attracts criticism from the media, consumer organisations, regulators and politicians, as recent examples in the US, the UK and Denmark have shown. It may also lead to regulatory intervention—the kind of publicity insurers would prefer to avoid.

Technology, experience and execution—it’s all there.

Discover why traditional tools such as Excel and legacy policy administration systems are no longer sufficient for modern insurance pricing. Learn how pricing engines enable faster deployment, greater data accuracy, regulatory compliance and the flexibility to respond to market changes.

With these solutions, insurers can reduce pricing risks, strengthen their competitiveness and achieve sustainable growth.

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