AI for Fintech
In financial services, model latency and explainability are not nice-to-haves — they are the product. We build real-time ML systems that score transactions in milliseconds, explain every decision, and hold up under audit.
- 47 ms
- fraud-scoring latency, down from 8 hours (PropCFlow)
- 92%
- precision on fraud detection
- $50M
- recovered for one client
Delivered in production
Sound familiar?
Fraud scoring that takes hours while losses accumulate in real time
Black-box models that compliance and regulators will not accept
Manual document processing bottlenecking onboarding and operations
What we build for fintech
Real-time fraud detection
Streaming pipelines (Kafka, Delta Lake) with ML scoring in tens of milliseconds — at hundreds of thousands of transactions per day.
Explainable ML
SHAP-based explainability built in, so every automated decision can be justified to compliance, auditors and customers.
Document intelligence
LLM-powered extraction from statements, KYC documents and contracts — cutting manual processing by 90%+.
MLOps & model governance
Automated retraining, drift detection and monitoring on Spark and Airflow — models that stay accurate after launch.
Proven in production
From 8 Hours to 47 Milliseconds: Real-Time Fraud Scoring at Fintech Scale
47 ms
Fraud-scoring latency, down from 8 hours
Read the PropCFlow Inc. story →
From Handwritten Deeds to $8.5M in New Leases: AI-Powered Mineral Rights Intelligence
90%
Faster deed processing
Read the Glacier Analytics story →
AI for Fintech — FAQs
Can you deploy inside our security perimeter?
Yes — everything runs in your cloud account with your access controls. Data never leaves your environment, and we work within your compliance requirements (SOC 2, PCI-DSS contexts).
How do you handle model explainability for regulators?
We build explainability in from day one — SHAP values for tree models, structured reasoning traces for LLM systems — plus decision logs designed for audit.
What latency can we realistically expect?
Our production fraud system scores at 47 ms end-to-end at 500K+ daily transactions. Sub-100ms is a realistic target for most real-time scoring use cases.
Do you work with early-stage fintechs?
Yes — the fixed-price Sprint model was designed for teams that need production-credible AI before they can justify a full ML team. Our Fractional CTO service also covers investor and due-diligence support.
Ready to talk fintech?
Tell us what you want to automate, build or improve. Our team will review your project and reply by email with practical next steps. No obligation.