title: Actuarial Model Point Generator
emoji: 🏗️
colorFrom: green
colorTo: red
sdk: gradio
sdk_version: 5.31.0
app_file: app.py
pinned: false
license: mit
short_description: Generate synthetic actuarial model points
tags:
- actuarial
- insurance
- model-points
- synthetic-data
- data-generation
- gradio
- dashboard
- excel
🏗️ Actuarial Model Point Generator
A flexible Gradio app to generate fully customized synthetic seriatim model points for use in actuarial testing, clustering, or analytics.
🌟 What’s New
This version adds complete UI control over generation logic:
- 👥 Number of policies (100 to 50,000)
- 🎲 Random seed for reproducibility
- 👶 Age range (min/max)
- 💵 Sum assured range
- 📆 Multiple selectable policy terms (5–30 years)
- 🧑 Include or exclude sex (M/F)
- 📦 Choose between fixed or variable policy count
🧮 Output Columns
Each generated row represents a policy and includes the following columns:
policy_id: A unique identifier for each policy, starting from 1.age_at_entry: Issue age.sex: "M", "F", or "U" (unspecified).policy_term: Chosen from selected terms.policy_count: Fixed (1) or random (1–100).sum_assured: Uniformly distributed between min/max.duration_mth: In-force duration, capped by policy term.
✅ How to Use
- Adjust your filters on the left.
- Click “Generate Model Points”.
- Preview the results in the table.
- Click “Download Excel” to save the data.
🧠 Use Cases
- Cluster-based model point selection
- Stress testing & actuarial simulations
- Product mix scenario planning
- Teaching or training actuarial students
- Model validation tools
📦 File Export
The download button exports the generated data table to an Excel file (.xlsx). The policy_id is included as the first column, and the DataFrame index is omitted from the file.
Warnings will be shown if inputs are invalid (e.g., min age ≥ max age).
🛠️ Local Installation
# Clone the repo
git clone [https://github.com/alidenewade/actuarial-model-point-generator.git](https://github.com/alidenewade/actuarial-model-point-generator.git)
cd actuarial-model-point-generator
# Install dependencies
pip install -r requirements.txt
# Run the app
python app.py
🙌 Acknowledgements
Huge thanks to the Lifelib community for their open-source contributions to life actuarial modeling in Python. This project draws inspiration from their work on model point clustering and stochastic modeling tools.
Check them out at: https://github.com/lifelib-dev/lifelib
📄 License
This project is released under the MIT License.
Created with ❤️ by @alidenewade for the actuarial analytics community.