Transaction Lookbacks and Monitoring via Network Modeling & Statistical Algorithms.  
Whittling down false positives in SARs & identifying anomalies and false negatives missed in SARs created by standard AML products. Complements your existing legacy solutions.

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A Fraud Monitoring & Detection Platform

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Banks struggle to keep up with new AML regulations, sanctions lists, investigative alerts, and investigation requests. They have to monitor, intervene, investigate and report potentially unlawful transactions. 

In the fight against money laundering, Banks waste Billions every year on false positives and in fines for false negatives 

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Our Differentiators

Algorithmic Techniques

Because patterns can run into thousands, understanding anomalies and conforming transactions is aided with various visualization techniques to help defend the final reports with regulators.

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What is the financial exposure as a result of AML? 

3-5% of Global GDP is laundered through the global systems. 

Penalties, alone,  was $1.2 trillion, and expected to increase by $400 billion in 2020.


Given the ever-growing sophistication of contra-parties, 95% of system generated alerts are “false positives”, requiring investigations (costly and time-intensive).

False positives cost billions of dollars in wasted investigation time each year but more importantly, expose banks to steep fines and reputational damage for failing to identify bad actors involved in organized crime sanctions evasion, or terrorism.

Our Solution

Topaz AML


Challenges with many of the existing AML products:

Consistent occurrence of false negatives.



Linear rule based techniques become brittle and are hampered by the multiple data privacy regulations.


Very high false positives.

Use TOPAZ-AML suite to dramatically reduce false positives and spot the real bad actors!


Business working with a foreign supplier

Scenarios We Tackle:

Business receiving or initiating a wire transfer request

Business contacts receiving fraudulent correspondence

Executive & attorney impersonation

Data Theft

Smurfing, Mule, Triage & Micro-segmentation, Nested Accounts and Other

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The TOPAZ - AML Promise:

Business Benefits

Turn the spotlight on suspected money laundering or fraud in hours instead of weeks.

Detect potential financial exposure with Topaz Real-time Monitoring service.

Insights and action recommendations on suspected transactions.

AI models often lack learning corpus which makes implementation very difficult. Solving this issue using SME defined taxonomies is key.  

Differentiated Machine Learning

Non-Linear Regression Models with Synthetic Data

Linear rule based become brittle over time due to lack of dynamic adjustment to non-linear patterns.

 Topaz AML’s non-linear modeling techniques adapt quickly, through self learning analysis. Topaz AML integrates with existing banking and AML systems, is efficient to deploy and scale, and maintains efficiency with near real-time update

Extensive logs to help audit the findings, including excel based outputs to help customize and integrate reports with existing regulatory SARs reporting infrastructure.


Topaz In Action!

Topaz AML Platform

Our learning algorithms take advantage of the large pools of data and heightened computing power available to detect patterns that might go unnoticed by data scientists.

in the context of the AML eco-system