Crux is an enterprise AI application scorecard platform designed for banks, fintechs, and digital lenders.
Improve GINI by 20+ points, increase approvals by 25%+, and reduce default risk — while maintaining full regulatory explainability and governance. Deploy live in under 24 hours. Zero coding required.
Increase in loan approvals without added default risk
GINI improvement over traditional scorecard methods
From data upload to live scorecard in production
Reduction in default loss rates across the portfolio
A complete AI-first toolkit for building, validating, and deploying high-accuracy application scorecards at enterprise scale — with no data science team required.
Blend logistic regression WoE scorecards with XGBoost ensemble ML. One click switches modes — full control is always yours, with no trade-off between interpretability and accuracy.
Connect bureau, transaction, CRM, and alternate data sources. Over 100 variables auto-derived with AI imputation and bias reduction built-in — no manual feature engineering.
Every approval or rejection has a transparent SHAP-based reasoning trail — critical for regulatory compliance, adverse action code generation, and model governance.
Fine-tune 20+ model parameters — binning strategies, PD calibration, variable thresholds — all without writing code. Business teams stay in control.
Deploy production-ready scorecards directly into your LOS via REST API. From final validation to live decisioning in a single click, with sub-second response times.
Track GINI, KS, and PSI drift alongside approval trends and default evolution — all on one live dashboard with automated retraining alerts when models need refreshing.
No months of data science sprints. Crux automates the entire scorecard pipeline end-to-end — so your team focuses on lending outcomes, not model infrastructure.
Whether you process 100 applications a month or 1 million a day — Crux scales to your lending operation without additional infrastructure.
Automate personal loan and credit card applications with enterprise-grade AI decisioning at scale.
Assess business loans using cash flow, social, and operational signals as predictive alternate data.
Millisecond credit decisions for embedded finance and buy-now-pay-later products at checkout.
Enrich bureau score products with AI-augmented decisioning models for member lending institutions.
Legacy models built on limited variables and manual development cycles leave approval rates low and defaults high. Crux's AI removes every one of those constraints — without adding complexity.
| Capability | Crux AI | Traditional |
|---|---|---|
| Model Build Time | Hours | 6–12 Months |
| Variables Used | 100+ Auto-Derived | 10–30 Manual |
| Explainability | ✅ SHAP Built-In | ❌ Manual Process |
| Alternate Data Support | ✅ Native | ❌ Not Available |
| No-Code Interface | ✅ Fully No-Code | ❌ Dev Required |
| Deployment Method | 1-Click REST API | Weeks of IT Work |
| Model Monitoring | ✅ Live Dashboards | ⚠️ Manual Reports |
| Regulatory Compliance | ✅ Audit Ready | ⚠️ Varies |
Model Performance Dashboard
Application Scorecard v3.2 — Live Production
An AI application scorecard is a machine learning-powered credit risk model that predicts the probability of default for loan applicants. Unlike traditional scorecards limited to static variables, AI scorecards analyse hundreds of behavioural, transactional, and bureau variables to improve predictive accuracy, increase approvals, and reduce portfolio risk.
Modern lenders use AI application scorecards to accelerate loan decisioning — from days to milliseconds — while maintaining full regulatory transparency, explainability, and governance through tools like SHAP-based adverse action codes.
Pair your AI Application Scorecard with other Crux intelligence products to cover the entire credit and decisioning lifecycle.
See a live demonstration of the Crux AI Application Scorecard — with your own data, your own portfolio, and your own risk thresholds.
Join banks, fintechs, and digital lenders already making faster, smarter credit decisions with Crux.