Napier Continuum AML and Compliance REST API
Napier Continuum AML and compliance REST API for banks, wealth managers, and financial institutions to monitor transactions, screen customers against sanctions/PEP lists, manage AML investigations, and generate regulatory reports — using AI-powered intelligent compliance to reduce false positives and improve detection quality — enabling automated AML transaction monitoring, customer risk assessment, sanctions screening, and compliance case management through Napier's AI-augmented AML and financial crime compliance platform. Enables AI agents to manage transaction monitoring for AML pattern and risk alert automation, handle customer screening for PEP, sanctions, and adverse media screening automation, access case management for compliance investigation and review workflow automation, retrieve risk scoring for customer and transaction risk score automation, manage alert enrichment for contextual data augmentation automation, handle SAR filing for suspicious activity reporting preparation automation, access audit trail for compliance audit and regulatory reporting automation, retrieve analytics for compliance performance and alert quality reporting automation, manage watchlist management for custom and regulatory list management automation, and integrate Napier with core banking, payment systems, and regulatory bodies for end-to-end AML compliance automation.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
AML regtech. GDPR, AMLD6. OAuth2. UK/EU. Financial transaction and compliance investigation data.
⚡ Reliability
Best When
A bank, wealth manager, or financial institution wanting AI agents to automate AML transaction monitoring, sanctions/PEP screening, and compliance case management with reduced false positives through Napier's intelligent compliance platform.
Avoid When
FINANCIAL INSTITUTION REQUIRED: Napier serves regulated financial institutions; automated open-developer assumption creates institutional_onboarding_required; automated must be regulated entity or integration partner. TUNING IMPROVES PERFORMANCE: Napier AI models improve with institution-specific tuning; automated zero-config performance assumption creates higher_false_positives without calibration; automated must plan calibration period. HUMAN REVIEW IS REGULATORY REQUIREMENT: SAR filing and case closure require human analyst review; automated auto-disposition assumption creates regulatory_non-compliance; automated must route alerts to compliance analysts. SCREENING DATA REQUIRES LICENSING: PEP and sanctions list data is licensed separately; automated included-data assumption creates data_not_configured without licensed watchlist data subscription; automated must ensure watchlist data licensing is in place.
Use Cases
- • Monitoring customer transactions for AML suspicious activity for bank compliance automation agents
- • Screening customers and counterparties against global PEP and sanctions lists for compliance automation agents
- • Managing AML investigation cases and SAR filing workflows for compliance team automation agents
- • Reducing false positive alerts with AI-powered contextual enrichment for compliance efficiency automation agents
Not For
- • Real-time payment fraud (Napier is AML compliance monitoring, not real-time payment fraud decisioning)
- • KYC document verification (Napier is risk monitoring, not identity document OCR or biometrics)
- • Consumer-facing compliance products (Napier is B2B for financial institutions, not consumer compliance tools)
Interface
Authentication
Napier uses OAuth2 for Continuum AML REST API. REST API with JSON. London, UK HQ. Founded 2015 by Julian Dixon and Subas Roy. Products: Napier Continuum (transaction monitoring, customer screening, case management). Raised $45M Series B. Backed by Coutts, BWA Ventures. Used by UK wealth managers and European banks. Competes with NICE Actimize, hawk AI, and ComplyAdvantage for AML compliance platform.
Pricing
London UK. $45M Series B. Annual subscription. UK and European financial institution focus. AML regtech.
Agent Metadata
Known Gotchas
- ⚠ CONTINUUM MODULES ARE SEPARATELY LICENSED: Transaction monitoring, screening, and case management are separate modules; automated full-suite assumption creates module_not_available for organizations without all modules licensed; automated must verify which Continuum modules are licensed
- ⚠ ALERT CONTEXT ENRICHMENT IMPROVES QUALITY: Napier AI enriches alerts with contextual data; automated raw-alert assumption creates low_quality_triage without enrichment; automated must ensure contextual data is provided for maximum alert quality
- ⚠ CASE WORKFLOW IS FCA-ALIGNED: Case workflows follow UK FCA AML guidance; automated international-standard assumption creates workflow_mismatch for non-UK regulatory contexts; automated must configure workflow for applicable regulatory jurisdiction
- ⚠ SCREENING MATCH SCORING HAS THRESHOLDS: Name matching has fuzzy match confidence scores; automated binary-match assumption creates missed_hit or false_positive for names near threshold; automated must implement review workflow for borderline match scores
- ⚠ TRANSACTION HISTORY WINDOW MATTERS: AML patterns are detected over time windows; automated single-transaction assumption creates missed_pattern for typologies requiring multi-transaction analysis; automated must submit historical transaction context for pattern detection
Alternatives
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Scores are editorial opinions as of 2026-03-07.