Eastnets SafeWatch AML vs Quantexa Entity Resolution

Eastnets SafeWatch AML is a web-based compliance product for financial institutions that monitors transactions and supports financial-crime investigations. It analyses transactions online in real time and examines historical transaction data offline. Unsupervised AI models assess account behaviour, surface anomalous activity, and generate alerts intended to reduce false positives. Dynamic risk scores for customers, accounts, and transactions help prioritise alerts. Users can select preconfigured AML scenarios or build rules with the Rule Builder and Library. Network analytics add relationship context that transaction-level monitoring may miss, and configurable workflows can reflect an organisation’s investigation processes. A built-in goAML module formats and submits reports according to United Nations standards. The modular system centralises transaction data from institutional sources in a dashboard and can expand as needs change. Eastnets says it supports FATF frameworks, EU Anti-Money Laundering Directives, and OFAC requirements. Onboarding includes integration, scenario configuration, and training, with ongoing regulatory updates and model recalibrations. Pricing is on request; the product page invites customers to request a demo.

Quantexa Entity Resolution links ambiguous records across people, organizations and places to build fuller profiles. Its machine-learning models match data incrementally, using available information and, where useful, context from third-party data. Machine learning and natural-language processing prepare structured and unstructured data through cleansing, parsing, transliteration and synonym handling, with models tuned for each country. Low-code, schema-less ingestion automates data mapping and handles complex nested data. The product supports batch matching and real-time resolution at request time, including household and organization matching. Quantexa says it can scale to tens of billions of records and reports 99% matching accuracy. It can be deployed on premises or in a preferred cloud, and connects with analytics environments, data lakes and warehouses through APIs and libraries. Identified uses include financial crime, anti-money laundering, customer intelligence and fraud. Fine-grained security can tailor responses to use cases and access rights. The web, API and self-hosted product is paid, with pricing on request.