CRiskCo Labs: Build Predictive Models Without a Data Scientist
CRiskCo Labs: Build Predictive Models Without a Data Scientist
A live product walkthrough — June 4, 2026
What if your credit, compliance, or finance team could build and deploy a production-ready machine learning model in under 30 minutes — without writing a single line of code, without a data scientist, and without waiting on IT?
That's exactly what CRiskCo Labs makes possible.
In this live session, we walk through the platform end-to-end: upload your data, define what you want to predict, train five models in parallel, and deploy a REST API endpoint ready for real-time scoring — all without touching engineering.
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How it works (5 steps, no code):
Upload your data — drag a CSV or connect via API. Labs accepts any mix of numeric, categorical, or date variables. No formatting required.
Define what you want to predict — select your target column. Labs auto-detects whether it's a classification problem (Will they default? Will they churn?) or regression (How much will they buy?).
Train 5 models in parallel — Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, and Neural Networks, all with automatic hyperparameter tuning. Zero configuration.
Compare and choose the best model — Labs surfaces AUC-ROC, accuracy, recall, Gini, and feature importance for each model so you can pick the right balance of predictive power and interpretability.
Deploy and scale — activate your model as a REST endpoint with API-key authentication for real-time scoring (<100ms latency), or download batch predictions. Monitor drift from the dashboard.
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What you'll see in this session:
How Labs auto-trains and compares 5 models on your own data
Real use cases: default probability, churn scoring, fraud detection, supplier risk, and AML/compliance alerts
How to enrich your models with SAT fiscal data for Mexican counterparties — signals unavailable in any credit bureau
Audit-ready explainability: how to justify model decisions to regulators and internal stakeholders
Live deployment to a REST API endpoint with sub-100ms latency
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Who should attend:
This session is designed for credit and risk analysts, compliance officers, CFOs, and finance teams who have historical data but lack a data science team to act on it. It's also ideal for compliance and AML teams, marketing and CRM teams, and anyone in operations or finance who wants to turn their data into predictions without depending on engineering.
No prior ML experience required. If you have a spreadsheet, you have everything you need to get started.
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Spots are limited. Register below to secure your seat.