Protecting financial institutions from systematic crimes

Kompligro is an AI-driven AML solution that sharpens the financial institutions’ detection systems.

Keep a close eye on customer’s financial activities with our transaction monitoring system. We help you to take faster decisions on suspicious high-risk activities and fight fraud while staying compliant.

Our AML solution is a configurable, end-to-end solution developed to handle enormous volumes of data, screen transactions, uncover layered patterns, and eliminate false positives. The solution utilizes advanced technologies including machine learning, cognitive analysis, robotic process automation, and artificial intelligence to provide a 360° view of the customer and generate Financial Crime Reports

Key Features

Sophisticated Rules Engine
Relationship Network Diagram
Key Features
Adaptive Behavioural Profiling
Pattern Recognition & AMP Anomalies


Speed Up AML Detections

By automating major chunks of the process, the solution reduces the time and effort spent on data gathering, prioritizes the highest risk alerts. This investigation and decision-making is fast- tracked through better insight into customer behaviour.

Improve Quality of Alerts

Integrating data across accounts, transactions and correspondence mitigates efficient detection system challenges like fragmented and multi-location data. The accurate data processing facilitates reliable reporting, reducing the probability of false positives by a great degree.

Reduce Operational Costs

Banks need not hoard human resources to deal with vast data volumes thanks to automation and machine learning mechanisms. The solution also saves time and effort on rework as human biases are removed from the processes.

Boost Overall Productivity

Comprehensive data gathering and processing results in elimination of time-consuming activities such as data entry and retracing investigation steps. Further, better data insights and reduced number of false positives allows analysts to focus on highest risk instances.

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