y 2035, no one in life insurance still talks about “running the model”.
That phrase belongs to an earlier era; a time when modelling was an event rather than a capability, when results arrived hours or days after questions were asked, and when insight lagged behind decision-making.
In 2035, modelling is simply there. Always on. Always available. And quietly shaping almost every material decision a life insurer makes.
For most UK life insurers, the last decade of financial modelling has been defined by regulation-driven urgency. Solvency II reshaped capital thinking. IFRS 17 then arrived and demanded industrial-scale reporting engines, new data flows, and an unprecedented level of modelling governance.
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.
As the complexity of models used by insurance enterprises continues to escalate, and the reliance placed on such models continues to grow, the importance of ensuring that models operate as intended comes under increased scrutiny.
Today, I’m excited to sit down with Pamela, Head of Insight Life Solutions to discuss her insights into the actuarial profession and her team’s experience with Mo.net.
This blog article introduces our latest paper, which presents a Mo.net powered solution that offers a streamlined approach for pension providers to align with the dashboard’s requirements.
Responding to a request from an existing client who wanted to connect their current Mo.net-based front office illustration platform with a new underwriting system, this blog article demonstrates how external API data sources can easily be used in a Mo.net model.
For years, there has been discussion about the use of graphics processing units (GPUs) to enhance the performance of financial models. Can GPUs represent a significant leap forward in the performance of financial models, or do the challenges and overheads outweigh the benefits?
Drawing from our recent experiences in assisting clients with the design and implementation of pension dashboard solutions, this post outlines how we’ve supported them and provides valuable tips on becoming “dashboard ready”.
The demanding regulatory environment increasingly places challenging stipulations around the number of model runs required and the timeframe in which results are to be produced. Combined with the ever-increasing volume of data that most insurers wish to process this can drive the need for a scalable model solution.