ChistaDATA is a data science and engineering company based in San Francisco Bay Area, that specializes in building data-driven solutions for Financial Services on ClickHouse. One of their recent projects involved building a real-time Anti Money Laundering (AML) system for the largest private bank in Europe using ClickHouse.
The bank had a massive amount of transactional data that needed to be analyzed in real-time to identify potential money laundering activities. The data included millions of transactions that needed to be processed every day, making it difficult to analyze the data in a timely and efficient manner. The bank needed a scalable and reliable solution that could process the data in real-time and provide insights to their compliance team to help them detect and prevent fraudulent activities.
ChistaDATA proposed a solution based on ClickHouse, a high-performance columnar database that is optimized for analytical workloads. ClickHouse was chosen because of its ability to handle large volumes of data, support for real-time analytics, and its ability to scale horizontally to accommodate growing data volumes.
The solution architecture involved the following components:
- Data ingestion: The bank’s transactional data was ingested into ClickHouse using Apache Kafka, a distributed streaming platform that can handle large volumes of data.
- Real-time processing: The data was processed in real-time using ClickHouse’s advanced query processing engine, which enabled the team to quickly detect and respond to potential money laundering activities.
- Machine learning: The solution also incorporated machine learning algorithms to help detect anomalous behavior and patterns in the data, enabling the team to identify suspicious transactions and take action.
- Dashboarding: A custom dashboard was created to provide the bank’s compliance team with real-time insights into the data, allowing them to take action quickly and effectively.
The solution provided the bank with several benefits, including:
- Real-time detection: The solution enabled the bank to detect potential money laundering activities in real-time, which allowed them to take quick action to prevent fraudulent transactions.
- Increased efficiency: The solution reduced the time and effort required to analyze the data, allowing the compliance team to focus on more critical tasks.
- Improved accuracy: The machine learning algorithms used in the solution helped to identify patterns and anomalies in the data that may have been missed using traditional methods, improving the accuracy of the detection.
- Scalability: ClickHouse’s ability to scale horizontally allowed the solution to accommodate growing data volumes without compromising performance or reliability.
In conclusion, ChistaDATA’s use of ClickHouse to build a real-time Anti Money Laundering system for the largest private bank in Europe demonstrates the power and flexibility of ClickHouse for handling large-scale, high-performance analytical workloads. The solution provided the bank with real-time insights into their transactional data, enabling them to detect and prevent fraudulent activities, and improving their compliance with regulatory requirements.