Quick facts
- Best for
- LLM-powered credit scoring that outperforms classical models.
- Pricing
- Paid
- Editor rating
- 5 / 5
- Community saves
- 0
About SquareGen
Socials: SquareGen installs proprietary GPT-style scoring systems inside lenders. We take your tabular credit, fraud, or portfolio data, translate it into a representation an LLM reads semantically, and fine-tune a model that produces calibrated default probabilities, a risk class, and a written rationale for every decision. The output reads like a senior analyst's note, not a feature-attribution chart, which makes it defensible in front of a risk committee, a regulator, and a board. Variables drop by 50 to 80 percent versus classical stacks, lowering bureau and data-source costs while keeping or beating incumbent AUC. The model lives inside your environment, runs without us, and is yours: weights, source, pipeline, and documentation transferred at close. It complements rule engines, scorecards, and machine-learning models you already operate rather than replacing them. PoC under NDA in two to four weeks, benchmarked against your incumbent on your own data. Supported featuresRun locally
Pros
- LLM technology for scoring
- Enhanced explainability
- Increased reliability
- Doesn't sacrifice interpretability
- More predictive platform
- Low complexity
- Robust performance
- Financial-grade reliability
- Efficient credit risk operations
- User-friendly experience
- Outperforms traditional models
- Fewer features required
Cons
- Only for credit scoring
- Dependent on LLM technology
- May lack extensive customization
- May need adjustments per country
- No transparency about updates