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    The Latest News & Insights from Software Alliance

Every few years, life insurance modelling circles back to a familiar idea: “Surely we can build this ourselves now?”

Open-source languages are mature. Cloud infrastructure is cheap and elastic. Numerical libraries are faster than ever. On the surface, the case for fully open-source financial modelling feels stronger than it ever has.

And yet, time and again, large-scale internal build attempts quietly stall, get re-scoped, or end up re-introducing vendor platforms through the back door. This isn’t because open source has failed actuarial modelling. It’s because life insurance modelling turns out to be much more than code.

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Over the last decade a number of free / open source database environments such as PostgreSQL and MySQL have emerged to challenge the traditional players like Microsoft SQL Server and Oracle.  Like PostgreSQL and MySQL, SQLite has found favour with lone developers using limited data sets or developing lightweight applications.  Even users of SQL Server Express Edition have moved to SQLite, where compatibility with the full edition of SQL Server isn’t a significant requirement.

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The U.S. insurance industry is undergoing a major shift in how it calculates statutory reserves for fixed annuity products. Leading this transformation is VM-22, a new reserving standard that officially became mandatory in 2025 for many non-variable annuities. With its adoption, insurers are moving away from traditional formula-based methods and embracing a more nuanced, principle-based approach—one that better reflects the complexity and risks of modern annuity products.

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In the life insurance industry, financial models—often built in complex spreadsheets—play a critical role in pricing, reserving, capital management, and strategic decision-making. These models are sophisticated, calculation-heavy, and require rigorous assumptions and projections over long time horizons. However, the very complexity that makes these spreadsheets powerful also makes them difficult to maintain, understand, audit, or transfer between teams—especially in the absence of proper documentation.

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It is not uncommon for multiple model developers to want to work on the same project. Changes made by each developer need to be added in to a central codebase to ensure there is always one source of the truth. Another common requirement is to be able to carry out code reviews, to check how one version of a model differs from the previous version, or to peer review an individual’s model developments.

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Abdi Ahmed

As the SAL platform continues to mature and grow and exciting new features are brought to market, ensuring that current functionality continues to work as intended becomes more important with every release. Manual testing continues to serve us very well here at SAL but a good testing practice requires a blend of automation and hands-on checks. We’ve been using an in-house bespoke automation tool to regression test our core product Mo.net Model Development Studio but have been in the market for a more comprehensive solution that offers reporting and ease of use for test development across the entire SAL suite of products.

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