Empowering Financial Institutions with AI-Driven Insights

At PureML Consulting, we transform complex data into actionable intelligence—optimizing fraud detection, customer personalization, and risk managementi.

Leveraging state-of-the-art graph ML and scalable predictive models, we uncover hidden fraud patterns, enhance underwriting accuracy, and drive revenue through intelligent product recommendations. Our end-to-end solutions are built on robust governance frameworks to ensure compliance and trust.

From real-time approval scoring to AI policy alignment with OSFI and the EU AI Act, our cross-functional expertise delivers measurable impact and sustainable growth. Let us help you harness the full potential of machine learning in your organization.

Data Strategy & Engineering

We design and implement robust data pipelines—ETL frameworks, data lakes, and real-time streaming—to ensure high-quality inputs for every ML model.

Model Development & Validation

From LightGBM and ensemble GLMs to graph-based ML, we build and rigorously validate predictive models, ensuring accuracy, interpretability, and resilience.

Deployment & MLOps

We containerize and deploy models with CI/CD pipelines, monitoring dashboards, and governance controls—so your ML solutions run smoothly and compliantly at scale.

Fraud & Risk Analytics

Uncovering complex fraud patterns with graph ML

Recovered $3M+ in confirmed fraud
Boosted detection accuracy by 45%
Delivered actionable insights to investigators

Real-Time Approval Prediction

Driving revenue growth with predictive scoring

Increased approval rates by 20%
Lifted revenue 15% across a three-sided marketplace
Integrated seamlessly via real-time APIs

Our Capabilities

Customer Personalization & Revenue Growth

Created a real-time model predicting approval likelihood for financial products — improved Borrowell’s revenue and approval success across a 3-sided marketplace.
Engineered “next best vertical” recommender from 100M+ analytics rows — increased conversion by 12% through smart routing to credit, insurance, and mortgage offerings.
Designed a loan pricing optimization model — lifted product revenue by 40% and improved targeting.

Predictive Risk & Financial Modeling

Developed a mortality model for pension annuity pricing — replaced table-based approach, restored trust after failed AI pilot, and streamlined quoting.
Built a LightGBM underwriting model for life insurance — reduced lab testing, accelerated processing, and influenced executive policy.
Delivered intra-fund cash-flow forecasting using GLM and ensemble methods — outperformed baselines and improved liquidity planning.

AI Governance & Global Validation

Led enterprise policy adaptation to OSFI E-23 — defined AI risk tiers, embedded GenAI testing (hallucination detection, adversarial prompts), aligned with NIST & EU AI Act.
Validated dozens of ML models (churn, claims, NLP, recommendation) across Canada, US, UK & EU — surfaced material flaws and replaced underperformers with challengers.

GenAI & Language Systems

Built early RoBERTa-based systems for sentiment analysis and document readability scoring — applied to regulatory review and voice-of-customer triage.

Additional Highlights

Architected and deployed crypto momentum bots & market predictors (2017, 2024–2025) — live auto-trading ensembles and Kaggle-derived signals.
Created predictive models for horse racing outcomes from GPS + betting data — developed invariant spatial features and tested real-market arbitrage potential.