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 the outcome you need. We’ll scope it, price it fixed, and deliver it — AI agents and senior engineers, one team.