Back in January, I outlined an approach for sourcing model assumptions at run time using a web data source. This approach used some custom code and a third party DLL to connect to the data source endpoint and digest the response. Following the release of Mo.net 7.7 this has just become much more straightforward.
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.
In the rapidly evolving landscape of the insurance industry, efficient and secure communication between stakeholders is more critical than ever. The Origo Messaging Standard has emerged as a powerful solution to streamline these interactions, particularly for insurance contracts.
Despite the importance of assumption management, many organisations still struggle to find a robust yet flexible solution to the problem and lack an effective assumption management framework.
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?
Software Alliance’s Su Berry spends 5 minutes with Cornelius Franken of CJF Consulting to discuss his experience with Mo.net and the benefits it has brought to his actuarial modelling processes.
As part of Mo.net 7.6, we have extended the external interface to compiled Mo.net tasks so that it now accepts a Python list. This update allows a new array of inputs to be passed from Python to the compiled Mo.net task DLL without having to create an intermediate inputs file.
In today’s complex and uncertain world actuaries are spending less and less time focused on the tasks they were hired to do. So, how did we get here and how do we fix it?