Why does insurance pricing software matter?

In the high-stakes world of insurance, pricing is the foundation of profitability and market competitiveness. A mere 1% improvement in pricing accuracy can translate to a staggering increase in revenue. Interestingly, insurance pricing could have 5-50x more impact on profitability than sales volume, as it was explained by Quantee's CEO here¹.

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The domain of insurance pricing is, however, not just one of the most impactful, but also one of the most sophisticated and complex within the industry. Insurance companies have spent decades refining their pricing strategies, always seeking to match real risks with competitive market rates. Let's explore how did it all started, what is the current state, and why insurance pricing software has become a thing.

The Evolution of Insurance Pricing

The journey of insurance pricing is a testament to the industry's relentless pursuit of accuracy and fairness. In the early days, pricing relied heavily on broad categorizations and the experience of underwriters. The traditional approach involved manual calculations and actuarial tables, with underwriters carefully evaluating risks based on a handful of data points. While effective for its time, this method was often time-consuming and prone to human error.

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As technology advanced, the insurance industry witnessed a significant shift towards automated pricing systems. The mentioned transition marked the beginning of a new era in insurance.  Pricing software products enabled faster, consistent risk assessments, resulting in precise premium calculations. This shift not only improved efficiency, but also reduced the potential for human bias in pricing decisions².  

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Today, insurers harness the power of big data, artificial intelligence, and machine learning to analyse vast amounts of information. The wealth of data enables insurers to create highly personalized risk profiles, offering more competitive rates to low-risk customers while better protecting themselves against potential losses.  

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The Complexities of Modern Insurance Pricing

In today's insurance landscape, pricing is a multidimensional puzzle that extends far beyond traditional risk factors. While data like age, location, and claims history remain important, they're just the tip of the iceberg. So, what are the other complexities?  

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Customer behaviour and market demand understanding

‍Great pricing is not just about accumulating more data points. The real complexity lies in understanding the intricate interplay between them. Insurers must understand how price changes affect customer behaviour and market demand, and this is where concepts like price elasticity and demand modelling come into play.

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Market dynamics and real-time adjustments

In a market where customers can compare quotes with a few clicks, pricing decisions must balance risk assessment with market competitiveness. Too high, and you lose market share. Too low, and profitability suffers. This market pressure and emerging risks (such as sudden spikes in cyber-attacks impacting cyber insurance) create the need for real-time pricing adjustments. As a result, pricing systems must be not just accurate, but also agile and responsive³.

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Regulatory

‍Insurance is a highly regulated industry, and pricing models must navigate a labyrinth of rules designed to ensure fairness and prevent discrimination. These regulations can vary significantly across jurisdictions, adding to the challenge for insurers operating in multiple markets.

Key Benefits of a Great Pricing Software

At some point in the insurance history, advanced pricing software has become a transformative force, offering distinct advantages that address the complexities we discussed earlier. Let's explore these in detail:
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Time to Market

‍Pricing software significantly reduces the time-to-market for implementing pricing changes. With integrated quotation engines and automated pricing modelling, insurers can swiftly adapt to evolving market conditions across various business lines, including motor, home, and travel insurance. This agility allows companies to respond promptly to competitive pressures and regulatory changes, maintaining their relevance in a fast-paced industry⁴.

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Governance and Auditability

‍Advanced pricing software offers robust governance and auditability features, enhancing transparency and compliance. Take, for example, functionalities like versioning, which tracks all performed actions and model changes or role-based access that enhance security and accountability, ensuring a smooth, auditable pricing process that aligns with industry best practices and regulatory requirements⁵.
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Pricing Accuracy

‍One of the foremost advantages of a great pricing software is its ability to enhance pricing accuracy through advanced analytics. While traditional Generalized Linear Models (GLM) remain foundational, modern pricing platforms leverage sophisticated machine learning algorithms including Gradient Boosting Machines (GBM) to capture complex non-linear relationships in risk assessment. These platforms can simultaneously process hundreds of rating factors, combining internal data with external sources through credibility models. The software's ability to integrate with external data sources enables insurers to enrich their risk assessment. This comprehensive approach ensures more precise risk assessment and pricing accuracy, particularly crucial in the property and casualty (P&C) and health insurance sectors.
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Portfolio Profitability

‍The ability to optimize portfolio profitability is another critical benefit of pricing software. These kinds of platforms often provide sophisticated price optimization and demand modelling features that help balance technical pricing with market dynamics. This way, insurers can improve combined operating ratios across customer segments, ensuring each portfolio segment contributes positively to overall profitability while supporting strong conversion and renewal performance.
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Explainability

‍Software can be helpful for increasing transparency and understanding through robust explainability features. For example, things like customizable chart visualizations allow to analyse data, diagnose models and perform impact analysis. This kind of functionalities not only aid users in grasping model behaviour but also facilitate effective communication of pricing updates to the stakeholders.
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Real-Time Portfolio Management

‍The ability to monitor and manage insurance portfolios in real-time is another significant advantage provided by modern pricing software. This feature empowers pricing executives to make instant business decisions in response to market changes such as new regulations or inflationary pressures. Real-time insights ensure that insurers can maintain a proactive approach to portfolio management, minimizing risks and capitalizing on opportunities as they arise.
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Efficiency of the Pricing Process

‍Finally, pricing software improves the efficiency of the pricing process, e.g., by enabling automated pricing modelling or facilitating collaboration within the team. This automation frees up valuable time for actuaries, allowing them to focus on strategic initiatives that drive innovation and competitive advantage. By streamlining operations, insurers can reduce costs and improve overall productivity within their organizations.

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How Modern Pricing Software Works

At its core, pricing software is a sophisticated ecosystem of interconnected components working in harmony to transform raw data into actionable pricing decisions. Let's dive into its key elements:

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Data Foundation & Infrastructure

The workflow begins with robust data management capabilities:

• Dataset Loading: Raw data ingestion from various sources through configurable database connections, supporting both cloud storage and SQL databases.

• Dataset Processing: Data cleaning, transformation, and enrichment with geographical data.

• Platform Extensibility: Custom, user-defined scripts integration through a plugin system, enabling specialized data transformations and business logic.
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Advanced Analytics & Modeling

The analytical core of the system consists of:

• Modelling Capabilities: Combination of traditional statistical approaches (GLM/GAM) boosted with AI-assisted functionalities to detect interactions and automate transformations as well as advanced, explainable machine learning algorithms. ‍
• Flexible Parameter Creation: Dynamic generation of customized modelling parameters through functions, lookup tables, and custom code to define modelling inputs, costs, and other assumptions with high flexibility. ‍
• Price optimization: Construction of comprehensive pricing models that maximize objectives while adhering to constraints.
  
  

Dynamic Pricing Engine

The heart of real-time pricing operations includes:

• API Integration: Exposure of pricing strategies to sales channels via online APIs.

• Flexibility: Support for both simple rating tables and complex ML models with online price optimization.

• Version Control: Tracking and audit capabilities for all pricing strategy updates.

• Testing & Personalization: A/B testing functionality for strategy validation, custom rules for customer-specific pricing, rapid price adjustments in response to market conditions.

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Output & Monitoring

‍The final stages ensure practical implementation and oversight:

• Dashboard Analytics: Interactive visualizations providing insights into the pricing pipeline.

• Portfolio management: Comprehensive tools for monitoring and managing the insurance portfolio performance.

• Reproducibility: Maintaining transparent and reproducible pricing processes.

This integrated approach enables insurers to maintain a dynamic and data-driven pricing strategy while keeping full control over their pricing decisions.

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Conclusion

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The evolution of insurance pricing from manual calculations to sophisticated software solutions reflects the industry's commitment to precision, efficiency, and innovation. As we've explored throughout this article, modern pricing software isn't just a technological upgrade—it's a strategic imperative that transforms how insurers approach risk assessment and portfolio management.

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The compelling benefits of pricing software—from enhanced accuracy and reduced time-to-market to optimized portfolio profitability and real-time management capabilities—demonstrate why it has become indispensable in today's insurance landscape. These systems enable insurers to navigate the complex interplay of risk factors, market dynamics, and regulatory requirements while maintaining a competitive edge and profitability.

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Looking ahead, the role of insurance pricing software will only grow in importance. As data sources multiply and market conditions become increasingly dynamic, the ability to harness advanced analytics, machine learning, and real-time optimization will separate market leaders from followers. Insurers who embrace these technological capabilities position themselves not just to survive but to thrive in an industry where pricing precision can mean the difference between profit and loss.

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I believe the future of insurance pricing lies in the continued evolution of these sophisticated platforms, so if you're already using pricing software or considering implementation, I'd love to hear about your thoughts and experiences. I'd welcome a conversation about challenges related to pricing software, please contact me at remigiusz.swiatkowski@quantee.ai

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References:

1. Dawid Kopczyk; https://www.linkedin.com/posts/dawid-kopczyk-quantee_do-you-know-that-insurance-pricing-can-have-activity-7163843199575154688-Pn9Z/?utm_source=share&utm_medium=member_desktop

2. Swiss Re, A History of Insurance; https://www.swissre.com/dam/jcr:638f00a0-71b9-4d8e-a960-dddaf9ba57cb/150_history_of_insurance.pdf  

3. Dawid Kopczyk, Agile insurance pricing: Rapid reactions to dynamic market events; https://www.quantee.ai/resources/agile-insurance-pricing-rapid-reactions-to-dynamic-market-events

4. Quantee.ai website, Use case: Reduce time to market for pricing changes; https://www.quantee.ai/use-cases/reduce-time-to-market-for-pricing-changes

5. Mind Foundry, Why Insurance Pricing Needs AI Governance; https://www.mindfoundry.ai/blog/ai-governance-in-insurance-pricing