AML Viewer

The AML Viewer provides a data-driven risk assessment workflow for compliance teams. It ingests structured customer and transaction data, applies jurisdiction-specific rules, and outputs a numeric risk_score, a risk_category, and a set of actionable flags with concise rationale. It supports onboarding checks, periodic reviews, and SAR preparation, helping teams document decisions and evidence for audits.
Conceptually, the tool combines rule-based scoring with anomaly detection across time windows and watchlist matching. Users can enable sanctions, PEP, and adverse-media modules, or operate with a minimal rule-set. Outputs are explainable: each flag references the triggering rule and its weight, and an audit_log records data lineage and processing steps.
Who benefits are banks, fintechs, and regulatory teams responsible for financial crime compliance, customer due diligence, and risk governance. The system emphasizes transparency and reproducibility, enabling regulators to trace decisions and produce SAR-ready narratives. It supports batch processing and export to standard formats for reporting.
Core features include configurable risk rules by jurisdiction, entity resolution, and watchlist cross-checks; anomaly detection across date and amount patterns; data validation and formatting; and audit trails with immutable records. The tool also supports localization for currencies, date formats, and data privacy requirements.
Use cases span onboarding screening, ongoing monitoring, and risk-based segmentation. The design prioritizes deterministic scoring, modular rule sets, and clear remediation paths. Unique value lies in its explainable scoring, ready-made compliance templates, and the ability to export governance-ready documentation.