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0.3. Innovation

It is very difficult to be truly innovative when you are restricted to closed source software.

While commercial pricing tools have their place, they are designed to fit the needs of many companies at once. That means they are built for the "average" pricing process - not for the unique strategy that could give your business a competitive edge.

Everyone using the same paid software has the same capabilities

If you are using the same pricing software as all your competitors - with the same risk factors, the same external data integrations, and the same modelling options - you are starting from an identical foundation.

When every insurer’s toolkit is essentially the same, any difference in strategy comes down to how the tool is used. But in practice, most teams use these tools in similar ways.

By moving to a more flexible, code-driven approach, you can design features, models, and workflows that competitors won't be able to replicate by simply using the same software feature.

Pricing complexity demands flexible solutions

Regulatory requirements, competitive pressures, and evolving distribution channels often mean pricing strategies are far more nuanced than the base capabilities of paid software allow.

This often leads to:

  • Workarounds that are cumbersome and hard to follow
  • Suboptimal pricing logic because the tool can’t handle the required complexity.
  • Decisions being constrained by the software rather than by the business need.

With code, these same nuances are often straightforward to build.

Leveraging advances in data science for pricing

The world of data science moves fast - far faster than most commercial pricing tools update.

Areas that have seen lots of development in recent years:

  • Machine learning techniques & explainability
  • Modelling workflows (MLOps)
  • Conformal prediction
  • Time series analysis
  • Geospatial analysis
  • Optimisation

These developments are often available in open-source Python libraries years before they appear in paid pricing software.

Being open source, these can also be a solid basis for building proprietary techniques.

Future-proofing your pricing capabilities

Code-based pricing workflows are inherently adaptable. As markets, regulations, and technology evolve, you can:

  • Modify your code to accommodate new rules or products.
  • Experiment with new modelling techniques without waiting for software updates.
  • Scale up processing power in the cloud as data volumes grow.

This means your pricing infrastructure can evolve with your business - rather than locking you into the release cycle of a software vendor.