Design a Reliable LLM-Integrated Interface for Mortality Forecasting

• URL: http://arxiv.org/abs/2606.06235v1
• Date: Thu, 04 Jun 2026 14:41:07 GMT
• Title: Design a Reliable LLM-Integrated Interface for Mortality Forecasting
• Abstract summary: This project proposes a reliable large language model (LLM)-integrated interface that improves usability while maintaining statistical power.<n>A three-phase methodology is employed to ensure accuracy, usability, and transparency.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Mortality forecasting plays an important role in actuarial and policy decision-making, but its implementation remains technically complex and inaccessible to non-expert users. This project proposes a reliable large language model (LLM)-integrated interface that improves usability while maintaining statistical power. The LLM is designed as a constrained orchestration layer that translates natural-language inputs into structured configurations for a deterministic forecasting pipeline. A three-phase methodology is employed to ensure accuracy, usability, and transparency. First, a baseline pipeline is implemented using the CoMoMo package, reproducing established mortality forecasting results. Second, the pipeline is extended to generate multi-step forecasts using rolling-origin evaluation and mean squared error (MSE). Third, a prototype interface uses a local LLM to handle users' forecasting requests in plain language. The system demonstrates that LLMs can enhance accessibility without compromising reproducibility, transparency, or actuarial validity in high-stakes analytical workflows.

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