About ExpertsLabel AI
We deliver expert-level annotation of:
Payment transactions
Banking and PSP data
eCommerce
order and refund flows
KYC/KYB customer data
Merchant risk data
Behavioral interaction logs
Our purpose is to fuel Agentic AI and Large Reasoning Models (LRMs) with the high-quality, multi-step reasoning traces needed to detect money laundering, terrorism financing, fraud, synthetic identity patterns, and emerging financial crime vectors.
Why Reasoning Data Matters?
Pattern comparison
across historical data
Multi-event dependency
reasoning
Backtracking and
hypothesis testing
This level of intelligence demands reasoning-grade annotated data, which ExpertsLabel AI provides.
Entity relationship tracking
Scenario simulation
Long-horizon logic
Our Specialisation: Financial and Regulatory Data
Our annotation specialists have backgrounds in:
AML Compliance
Transaction Monitoring
KYC/KYB Onboarding
Banking Operations
FinCrime Investigations
eCommerce Risk Management
Audit and Regulatory Reporting
This ensures that labeled datasets reflect real-world regulatory expectations, not just generic ML categories.
We also stay aligned with frameworks such as:
FATF recommendations
EU AMLA guidelines
AMLD6 and
PSD2 / PSD3
DORA frameworks
Local FIU reporting standards
OFAC/EU
sanctions screening expectations
Why Companies Choose ExpertsLabel AI
Differentiators:
Our experts bring extensive knowledge of banking, compliance, and financial systems. This specialisation strenghten our precision in finance-related projects.
Our annotation process captures logical reasoning steps, enabling advanced model understanding. This approach ensures data reflects both outcomes and the thought process behind them.
We develop precise rules to identify money laundering, terrorist financing, and fraud patterns. These rules align with compliance standards and adapt to everchanging risk scenarios.
Complex reasoning is accurately represented through multi-step labeling. This improves model performance for tasks requiring detailed logical analysis.
We provide complete evaluation services for models aligned with human feedback and preferences. Our process covers data collection, testing, and performance measurements.
All operations adhere to strict financial data protection and regulatory requirements. This guarantees secure handling of sensitive information across every stage.
Our teams operate worldwide, ready to scale for projects of any size. This flexibility ensures timely delivery without compromising quality.
Automated quality checks maintain accuracy and consistency across datasets. AI-driven validation reduces errors and improves reliability.
We maintain continuous, secure operations to support critical workflows. Round-the-clock availability ensures uninterrupted service and data protection.
Quality Assurance
Multi-layer review workflows
Inter-annotator agreement metrics
Automated anomaly detection
Calibration sessions with AML experts
Red-teaming of reasoning datasets
Future Roadmap
Real-time Labeling
Continuous AI-assisted labeling pipelines for live data streams.
Synthetic Crime Scenarios
Generate novel fraud & AML patterns to improve detection models.
Hybrid Annotator Systems
Self-improving loops combining human expertise with adaptive AI.
Domain-Specific LRMs
Specialised language-risk models tailored for financial crime.
Global Fraud/AML Ontology
Unified risk knowledge graph spanning fraud, AML an sanctions.
Multi-Modal KYC Reasoning
Cross-modal analysis using text, documents, images and graphs.
