NON-BANKING ENTITY

Static AML +

SILENICA has developed rule based AML + system and fine tuning tools, to improve the effectiveness based on the number of true positives.

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TRANSACTION MONITORING

ML AML +

SILENICA offers transaction machine learning AML system to take AML beyond what rule based systems can do.

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01
RULE BASED SYSTEM

Static AML +

SILENICA has developed rule based AML + system.

RELIABLE

Risk based approach

Incorporating not only activitiy of the client but as well customers' risk elements of the KYC and other specific risk elements.
MODIFIABLE

Qualitative & Quantitative Tuning

Implementing Gap analysis and Statistical Tuning
DISTINCT

Client specific

Implementation of Population Group to the Transaction Monitoring Scenarios
BEST PRACTICES

Suppression Logic

Implementation of a Suppression Logic to the Transaction Monitoring Process

Ready to get Started?

Detect frauds and money laundering.

OPENING

Rule Based AML +

AML system implementing static rules and best avaliable practices.
OPENING

ML AML +

AML system based on Machine Learning algorithms.
02
TRANSACTION MONITORING

AML +

SILENICA offers transaction machine learning AML system to take AML beyond what rule based systems can do.

POWERED BY

Machine Learning

AML powered by machine learning
DEVELOPED BY

Experts

Developed by experts in financial services and IT banking solutions
RESULTS CAN BE

Eeasily reproduced

Models designed in a way that allows for results to be reproduced given the same input
EXPERIENCED

Model Validators

Experienced model validators

Ready to get Started?

Coming soon.

About
Silenica

About us

SILENICA has two distinct business areas:
  • >Static AML +
  • >Development of AML + machine based transaction monitoring system

Do you have any question?

Please contact us directly by mail or from our contact form. You can also visit our support page which might help solve your problem.
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