Building a high-performance in-house life projection and ALM model: Architecture and implementation considerations in Python
Designing and building a custom life insurance projection and asset and liability management (ALM) model in-house is a challenging endeavour that many insurance companies are considering. This white paper investigates numerous challenges and decisions that must be taken regarding the architectural choices that fit different functional requirements, as well as implementation approaches that ensure high performance and code simplicity. In the paper, we discuss:
- The temptation of an in-house model and risks involved
- Architectural and functional choices in cash flow projection models
- Information technology landscape
- Implementation in Python
- Our benchmark
Explore more tags from this article
About the Author(s)
Contact us
We’re here to help you break through complex challenges and achieve next-level success.
Building a high-performance in-house life projection and ALM model: Architecture and implementation considerations in Python
With the right expertise, designing and implementing an in-house life projection and ALM model using Python can yield significant model performance improvements.