Financial trading floor
Financial Services

AI that moves at
market speed.

Fraud detection, risk modeling, compliance automation — we build AI systems for institutions where milliseconds and basis points matter.

99.97%
Fraud detection rate
$180M+
Fraud prevented annually
8
Tier-1 banks served
What We Build

Financial AI capabilities

Purpose-built AI systems for institutions that cannot afford to be wrong — where compliance is mandatory and performance is measured in milliseconds.

Real-Time Fraud Detection

ML-powered transaction monitoring that catches fraud in milliseconds, not days.

Algorithmic Risk Modeling

Credit risk, market risk, operational risk — quantified and actionable.

Regulatory Compliance Automation

AML, KYC, SOX, GDPR — automated reporting that keeps regulators satisfied.

Portfolio Intelligence

AI-driven insights for asset allocation, rebalancing, and performance attribution.

Predictive Credit Scoring

Alternative data models that assess creditworthiness beyond traditional metrics.

Secure Infrastructure

SOC 2 Type II, PCI DSS, bank-grade encryption. Security is not optional.

Case Study

Tier-1 Investment Bank Fraud Overhaul

How AI-powered fraud detection achieved 99.97% accuracy while reducing false positives by 97% — preventing $41M in annual losses.

The Challenge

A tier-1 investment bank processing $2.4B in daily transactions was hemorrhaging money to fraud — $47M annually in direct losses, plus reputational damage. Their rule-based fraud detection flagged 12,000+ transactions daily, but 94% were false positives, creating alert fatigue. Real fraud slipped through. Regulators were circling. The board demanded a solution within 6 months.

Our Approach
Phase 1Risk Assessment2 weeks

Analyzed 18 months of transaction data, fraud patterns, and false positive triggers. Mapped regulatory requirements across 14 jurisdictions.

Phase 2Model Architecture4 weeks

Designed ensemble ML model combining real-time behavioral analysis, network graph patterns, and historical anomaly detection.

Phase 3Training & Validation5 weeks

Trained on 2.1B historical transactions. Achieved 99.97% detection rate with <0.3% false positive rate in backtesting.

Phase 4Integration & Testing4 weeks

Integrated with core banking, SWIFT messaging, and compliance systems. 30-day parallel run with existing system.

Phase 5Deployment & Tuning3 weeks

Phased rollout by transaction type. Real-time model retraining pipeline for emerging fraud patterns.

18 weeks from kickoff to production
12 HNL engineers + 4 bank risk analysts
Outcomes
99.97%
Fraud detection rate
Up from 82% with rule-based system
$41M
Annual fraud prevented
Direct savings in first year
97%
False positive reduction
From 94% to under 3%
340ms
Average detection time
Real-time transaction scoring

Ready to modernize your financial infrastructure?

Let's discuss how AI can reduce risk, accelerate compliance, and give your teams the intelligence they need to compete.

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