Monitor transactions with unparalleled speed and precision

Anti-Money Laundering software

Anti-Money Laundering is a fraud detection software dedicated to financial institutions obligated to monitor, investigate, and report-  transactions of a suspicious or unusual nature to financial investigation units. It optimizes the existing anti-money laundering processes by significantly enhancing the effectiveness of most commonly used – and inefficient – rule-based approaches, characterized by high false-positive rates and the nability to consider complex interdependencies between various activities carried out to launder money.

Here are the most important results we have noted while cooperating with banks:

Key business advantages

Fewer false alarms, more insights

Dots connected faster and better than any human can

Cost reduction

Greater efficiency of AML departments = operating costs going down

Risk-based approach

Measures to prevent money laundering always corresponding with the risks identified by your institution

No need to replace your AML system

Quick and easy integration with banking systems

State-of-the-art technology

AI-based, self-improving solution that never goes out of date

Prioritize tasks and get a head start thanks to SARs

Terminate bogus bank accounts faster

How it works

Enhanced detection process with Comarch AML software

AML software analytical engine

At the heart of Comarch’s AML software is an analytical Artificial Intelligence (AI) engine that processes data streams and detects money laundering activities. The scope of operations being monitored is broad and covers deposits, withdrawals, purchases, fund transfers, merchant credits, payments, trading activities, and investments. The engine leverages most recent supervised and unsupervised learning techniques to discover anomalies and improve the detection breadth.

Data pre-processing

Before the AI engine can correctly analyze bits of information and draw conclusions, it needs properly prepared data. The process of getting data ready for an anti-money laundering program requires several preparatory activities. The key step of data preparation is a transformation which typically involves scaling, decomposition and aggregation. This step is also referred to as feature engineering, and, if properly carried out, can be very beneficial to the performance of the final solution. Data preparation is a broad subject that can involve a lot of iterations, explorations and analyses. The data pre-processor module is responsible for integration with data sources existing in financial institutions’ databases and the correct introductory processing and transformation of data which will be subsequently analyzed in the AI engine.

Performance monitoring

The money laundering process evolves over time, and new advanced fraud patterns appear, which makes it necessary to constantly monitor the solution’s performance. As new data arrives, the algorithms that were trained based on historical data may require periodical re-training (e.g. in the case of sudden increase in the number of false alarms). The monitoring module is responsible for gathering statistics, analyzing results and warning about any unusual performance loss.

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