Squaregenai

What is SquareGen?

SquareGen is an innovative tool that delivers state-of-the-art LLM-based credit scoring. It is designed to outperform traditional credit scoring models by utilizing fewer features while providing deeper explainability and financial-grade reliability. Unlike classical models, SquareGen reimagines how credit risk is measured, ensuring stable and deterministic outputs, true probabilistic risk assessments, and a significant performance edge over conventional methods.

How to use SquareGen?

1. Import the SquareGen library in your Python environment using `from squaregen import SquareGen`.
2. Initialize the model by providing your training and testing data files: `sg = SquareGen("train.csv", "test.csv", target="target")`.
3. Select the desired number of features to use for scoring: `sg.select_features(n_features=45)`.
4. Train the model using your selected features and specify the model type: `sg.train(model="SquareGen-R1-Nano", epochs=2)`.
5. Explain the model's predictions by examining a few cases: `sg.explain(n_cases=5)`.
6. Benchmark the model performance based on the feature count: `sg.benchmark(feature_count=20)`.

What are the main features of SquareGen?

• LLM-based credit scoring that outperforms classical models.
• Requires 50-80% fewer features, enhancing efficiency.
• Offers deeper explainability through interpretability from attention layers.
• Provides true probabilistic outputs calibrated for proper AUC extraction.
• Demonstrates radical feature efficiency by reducing noise and leakage risk.
• Consistently improves AUC by 2 to 10 percentage points over gradient boosting models.

Who is SquareGen for?

SquareGen is tailored for financial institutions, credit agencies, and businesses involved in lending and credit risk assessment. Its advanced capabilities make it suitable for data scientists, risk analysts, and financial professionals who require reliable and explainable credit scoring solutions. The tool is particularly beneficial for organizations looking to integrate modern AI techniques into their credit scoring processes while reducing operational complexity.

What are the use cases of SquareGen?

1. Enhancing credit assessments for small and medium enterprises (SMEs) with improved scoring accuracy.
2. Streamlining consumer loan approvals by utilizing fewer features for faster processing.
3. Integrating with existing risk frameworks to provide robust credit scoring solutions.