AI TOOL PROFILE
EyesClear: AML Transaction Monitoring Software
- Finance and Accounting
- Compliance Management
- Retail Banks
- Broker-Dealers
- Payment Service Providers
- Asset Managers
- Cryptocurrency Exchanges
Pricing
Pricing was not clearly available from the provided evidence. Buyers should confirm current pricing on the vendor website.
At a glance
- Best for
- Retail Banks, Broker-Dealers, Payment Service Providers, Asset Managers, Cryptocurrency Exchanges
- Key use cases
- Retail Bank Cross-Channel Monitoring, Broker-Dealer Trade Surveillance, Payment Provider Money Mule Detection, Crypto Exchange Travel Rule Compliance, Asset Management Due Diligence
- Integrations
- Apache Kafka, ActiveMQ, IBM WebSphere MQ, SWIFT, ISO20022
- Official website
- Visit EyesClear official website
How AI is used
EyesClear is a real-time anti-money laundering (AML) transaction monitoring platform designed for financial institutions. It integrates a data lake, alerting system, and case management tool into a single architecture that supports processing up to 10,000 transactions per second.
The software is designed for compliance, treasury, and audit teams at retail banks, broker-dealers, payment providers, and cryptocurrency exchanges. It supports both cloud and on-premise deployment to help meet specific local regulatory requirements.
Key capabilities include the use of Large Language Models (LLMs) to assist analysts with SAR narrative generation and a chatbot for platform support. The system allows users to reprocess historical data using updated detection typologies, which may reduce manual setup work when regulations change.
Buyers should confirm how the technical requirements align with their internal infrastructure and whether the on-premise or cloud deployment options best fit their jurisdictional compliance needs.
Key Features
Real-time Alerting
Triggers alerts as transactions flow through the system.
LLM SAR Generation
Uses AI to draft Suspicious Activity Report narratives based on case details for analyst review.
Network Analysis
Identifies clusters of related accounts and relationships without requiring a separate graph database.
Historical Typology Application
Supports applying new detection rules across transaction histories for retrospective review.
Case Management Workflow
Includes risk-based routing and automation to manage alerts from detection to resolution.
AI Data Lake
Provides a unified data foundation that supports ingestion of up to 100,000 data points per second.
Use Cases
Retail Bank Cross-Channel Monitoring
Unifying deposits, withdrawals, and card transactions from branches, ATMs, and mobile apps into one view.
Broker-Dealer Trade Surveillance
Monitoring trading patterns in real time to identify wash trades, spoofing, and unusual volumes.
Payment Provider Money Mule Detection
Using network analysis to identify hub accounts used to forward funds.
Crypto Exchange Travel Rule Compliance
Monitoring originator and beneficiary information for transfers to support FATF-aligned requirements.
Asset Management Due Diligence
Using relational parsing to link entities across ownership chains for investor onboarding.
Integrations
- Apache Kafka
- ActiveMQ
- IBM WebSphere MQ
- SWIFT
- ISO20022
- PostgreSQL
- Oracle
- IBM DB2
- Microsoft SQL Server
FAQ
What is EyesClear used for?
- EyesClear is used by compliance and operations teams at financial institutions to detect and investigate suspicious transactions in real time.
Does EyesClear use AI in its compliance workflow?
- Yes, it uses Large Language Models (LLMs) for drafting SAR narratives, providing an analyst support chatbot, and generating reports.
Can EyesClear be deployed on-premise?
- Yes, the platform supports both cloud and on-premise deployment to help institutions meet local regulatory requirements.
Source category: Finance & Accounting
Source subcategory: Compliance Management
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