Under Construction — Launching Soon
The intersection of LLMs and Financial Crimes
Cove Labs is building the next generation of AI-native tools and processes for fraud and AML — purpose-built for LLM researchers, LLM data providers, banks, Fintechs, and regulatory teams. While frontier LLMs can be extremely useful tools, Cove Labs' research has shown that LLM models do not have adequate training for financial crime. Check back in a few days for our full platform launch.
To request a summary of our research, please complete the request below.
The Problem
Financial Crime Is a Trillion-Dollar Crisis
Legacy detection systems were not designed for modern, cross-border, multi-layered financial crimes - now exacerbated by bad actors leveraging AI tools. Rule-based engines generate overwhelming false positives, investigators are understaffed, and sophisticated typologies evolve faster than compliance teams can respond.
$500B
Annual Global Fraud Losses
Estimated annual losses from fraud across all financial sectors worldwide
$1–2T
Money Laundered Annually
Global estimate of illicit funds laundered through the financial system each year
Sources: Interpol 2026, TransUnion 2025, UNODC
Our Expertise
Deep Financial Crimes Domain Knowledge
Our team brings an average of 15+ years of hands-on experience in financial crimes — spanning fraud, AML, sanctions, and regulatory compliance — across the full spectrum of financial institutions.
Banks & Credit Unions
Strategy and analytics for enterprise-scale fraud and AML programs at top-tier global banks
Fintechs
Fraud and compliance program design and enhanced detection for high-growth platforms
Wealth & Insurance
Risk and compliance frameworks and implementation for wealth management, insurance, and investment firms
Leadership
Built by Industry Veterans
Our founding team includes former executives from some of the most recognized names in financial services and fraud technology — bringing operational credibility and deep institutional knowledge to every engagement.
Former Bank of America Payments Executive
Experience across the Consumer & Small Business and Commercial & Corporate businesses; US and global responsibilities
Former Data Science Executive at FICO
Credit card and payments modeling and machine learning at scale for fraud detection, as well as account opening and account takeovers
Former Executive at Discover & HSBC (Advisor)
Senior business and risk executive with experience owning Fraud & AML, including global risk strategy and sanctions compliance
Technology Focus
LLMs Trained for Financial Crime
While frontier LLMs can be extremely useful tools, Cove Labs' research has shown that LLM models do not have adequate training for financial crime. Cove Labs applies Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) to large language models — enabling them to detect, investigate, and explain complex financial crime typologies with far greater precision than traditional systems.
This methodology ensures models are not just accurate, but observable, explainable, auditable, and aligned with regulatory expectations.
Use Cases
Targeting High-Impact Fraud & AML Scenarios
Fraud Detection
- Identity Theft & Synthetic Identify Fraud
- Account Takeover
- Payment Fraud (all payment types)
- First Party Fraud
- Real-time Transaction Monitoring
AML & Financial Intelligence
- Transaction Monitoring & SAR Generation
- Sanctions Screening & Name Matching
- Customer Due Diligence (CDD / EDD)
- Network Analysis
- Typology Detection
Our Approach
How We Enable LLMs for Financial Crime
We combine domain expertise with cutting-edge application of LLMs to build models and AI agents that understand the nuance of financial crime — not just patterns, but intent, context, and regulatory logic.
01
Domain-Curated Training Data
Labeled fraud and AML datasets built from real-world typologies and investigator knowledge
02
Supervised Fine-Tuning
SFT on task-specific financial crime scenarios for high-accuracy detection
03
Reinforcement Learning
RLHF loops incorporating investigator feedback to continuously improve model performance
04
Explainable Outputs
Audit-ready reasoning and SAR-ready narratives generated alongside every alert
Why Cove Labs
The Right Team at the Right Moment
The convergence of mature LLM capabilities and persistent gaps in financial crime detection creates a rare window. Cove Labs is uniquely positioned — with the domain credibility, technical depth, and institutional relationships — to lead this transformation.
Proven Track Record
20+ fraud and AML engagements executed across major financial institutions
AI-Native by Design
Built from the ground up for LLMs — not a retrofit of legacy rule engines
Operator Credibility
Former executives from BofA, FICO, Discover, and HSBC who have lived the problem
Global Scope
Experience spanning US, UK, and international financial crime regimes
Get Involved
Let's Build the Future of Financial Crime Detection
We're engaging with frontier LLMs, banks, fintechs, regulators, and research partners who share our conviction that LLMs can fundamentally transform how financial crime is detected and investigated. Reach out to start the conversation.
Partnership Inquiries
Open to collaborations with financial institutions, data providers, and AI research teams
Stay Updated
Check back soon — our full platform and research publications are launching shortly
Hiring
Building a team of passionate Financial Crime experts and practitioners