Unify your AML compliance strategy

Unify enterprise-wide transaction monitoring for a holistic view of risk

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Table displaying risk levels across organization units Asia Pacific, Europe, and Group, with risk categories Standard, Low, Medium, High, and corresponding numerical risk model ranges under columns Risk model 1000 To Value and Risk model 1001 From Value. Three blue buttons on the right labeled Edit Risk Model, Compare Production Risk Model, and Risk levels for Editable Risk Model.
NetReveal AML Suspicious Activity Alert interface showing user Noureddine Darib Noureddine. The Sensa Explanations tab displays risk metrics like Overall Risk Score 83, Risk Similarity 80, Anomaly Detection Score 94, and Hotspot Score 80, with features and values for transactions such as Total 3 Month Domestic Debits 2183.22 and Wire from Known Tax Haven 23640.00. Subject details show personal info including identity, category, tax number, address, email, gender, birth date, and occupation. A tooltip highlights that explanations for the Risk Similarity Score are accessible within the alert.

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Take a tour of the admin capabilities available that enable managers to create and control queues, teams, and workflows with ease.

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Two overlapping charts showing detections per scenario and a scenario report with number of detections as 1; bars display Org Unit as GRO(100%), TP FP as UNK(100%), and Customer Segment as CORP(100%). The chart on the left lists AML scenarios with detection percentages, led by AML30 A high amount transaction at 40.3%.

Rapid deployment in 12 weeks

Seamlessly deploy enterprise-wide for multiple lines of business across complex organizational structures in just three months.

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Bar chart showing Actioned Rate for three categories: CORP at 109.00, PERS at 788.00, and SME at 440.00, with a side panel listing AML scenarios like calculating risk scores and monitoring transactions.

Flexibly scale

Engineered to handle extreme volumes of data and effortlessly scale to match the needs of even the largest financial institutions.

Bar chart showing count of detections by region: Asia Pacific 8, Europe 119, Group 396, North America 47, Shared 49, South America 40. An overlaid score range chart shows multiple ranges mostly between 50 and 100.

See the bigger picture

A centralized view quickly identifies sophisticated criminal behaviour that remains hidden to siloed teams, enabling more effective risk mitigation.

Partial screenshot showing a table with columns for Code, Name, and Type listing workflow actions and screen rules, alongside a bar chart titled Customer Segment with segments PERS (78%), SME (18%), and CORP (3%).

Unrivalled compatibility

Integrate seamlessly into your tech ecosystem and keep your compliance strategy agile and ready to evolve when needed.

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SymphonyAI Investigation Hub interface showing an AI investigation summary for John Rolands, labeled with personal subject ID CUST-T2423 and a very high subject risk. The summary details Joe Rolands as a politically exposed person with a high-risk level and 80 detections including multiple cash deposits. Tabs include AML, KYC/CDD, Payment Risk, and Customer Screening. The detections list shows five daily events titled 'AML08 Several cash deposits as different branches' from March 27, 2023, with due dates April 27, 2023, and varied outcomes of unusual and not unusual, all reviewed on March 27, 2023. Assignee is Leopoldo Boutique.
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Take risk and compliance consolidation to the next level

Unify enterprise-wide risk detection across AML, KYC/CDD, sanctions screening and payment fraud for an unparalleled single, subject-centric view.

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Solution benefits

Reduce exposure to risk

Identify and mitigate hidden risks that others may overlook thanks to advanced ML and AI models.

Reduce false positives

Significantly decrease false positive alerts, saving valuable time and resources.

Improve investigator efficiency

Streamline operations, automate manual tasks, and provide a holistic view of risk.

Future-proof compliance

Stay ahead of evolving regulatory requirements and industry standards with advanced AI.

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