Entity Resolution

Resolve every data point straight out-of-the-box

Resolve disconnected data and transform billions of siloed data points into a unified customer view

A large translucent pale blue gradient circle on the right side fading into white.
Screen showing a customer list with details for four subjects including IDs, names, and CDD risk levels. One subject named Sarah Winters is selected, showing detailed identity and financial profile on the right, including personal info like address, email, phone, gender, birthdate, occupation, and risk factors such as source of funds and sanction status. Sarah Winters is marked with high CDD risk and not sanctioned.

Create a single subject for risk investigations

Consolidate disparate customer information into a single source of truth for a clearer understanding of their behaviour and relationships with others.

Side-by-side comparison of personal details for Sarah Winters and Emily Schwarz with high CDD Risk; both female in retail category born on 17/07/1994, Sarah employed at Tees Engineering Ltd with Visa ID (LKCRCRX620176740, KY), Emily unemployed with unknown employer and other ID (YOBCW96302347619, AZ), main address shared as 18 Redway Street, Washington DC, US.

Resolve duplicate records in minutes, not hours

Quickly identify multiple records of the same customer and stop new duplications being created. Side-by-side views of related accounts enable investigators to swiftly resolve duplicate accounts.

User interface screen showing customer Sarah Winters' alerts, with a list of two alerts and a visual relationship map linking Sarah Winters to multiple individuals including Michael Johnson and Kathy Howard, highlighting suspicious activity and customer due diligence alerts.

Pre-packaged for immediate results

Delivering rapid results out-of-the-box, Entity Resolution easily integrates into existing workflows to start delivering actionable insights.

Diagram showing the central entity Duran Enterprises connected to individuals and groups with labels indicating relationships such as owner, beneficiary, main subject, secondary, and share ownership. Peter Gadet-Leroux, Peter Gadet, Allistair Woodsworth, David Elliot, and PGL Group are linked with various ownership and beneficiary roles, along with identifiers CDDRT2023121546949, A2023110821849, and A2023103161730 marked as main subjects.

Visualize complex customer relationships

Follow the money to uncover concealed relationships and expose criminal networks hidden within diverse records from internal and external data sources.