FutureFlow // Secretarium
Powering Financial Crime Analytics
As financial institutions grapple with the challenges of detecting and preventing financial crime within strict regulatory frameworks, there’s a need for innovative solutions.
FutureFlow and Secretarium proved what was possible with the Amlytic platform, a cutting-edge privacy-preserving solution for cross-bank financial crime analytics.
Their success was enhanced by Syntheticr 2.0, providing the foundation for developing, testing, and demonstrating the platform, that has now won a prestigious G20 award.
Financial institutions typically rely on sensitive personal data, such as Know Your Customer (KYC) information, to detect financial crime, but sharing this data across banks presents substantial regulatory and privacy challenges.
Also, institutions often encounter issues with incomplete or inaccurate data, hindering their ability to build robust analytics models that can effectively detect criminal activities.
Syntheticr 2.0 provided high-quality synthetic data that accurately represented financial transactions without the risks associated with personal information.
This allowed FutureFlow and Secretarium to develop, test, and demonstrate the Amlytic platform safely and effectively including:
The synthetic dataset included simulated bank transaction data, enabling FutureFlow to model complex cross-bank transactions and ensure that the platform could effectively handle scenarios indicative of financial crime.
Testing Real-World Scenarios
By anonymizing the synthetic data, FutureFlow and Secretarium proved adherence to GDPR and other privacy regulations from the outset, demonstrating the platform's capabilities in a compliant and secure environment.
Ensuring Privacy Compliance
The development and demonstration of Amlytic, powered by Syntheticr 2.0, was instrumental in securing a G20 award for showcasing the platform’s potential to detect suspicious activities without the use of customer data.
Achieving Global Recognition
The Amlytic platform empowers multiple banks to collaboratively analyse suspicious transactions in real time.
By focusing on the flow of funds instead of sensitive personal information, it delivers powerful insights while safeguarding data privacy.
The Amlytic platform has a unique range of key features including:
Syntheticr 2.0's synthetic data enabled continuous development and enhancement of the platform’s advanced machine learning algorithms, designed to analyze transaction networks for signs of suspicious activity.
Data-Driven Development
Adopting privacy-by-design principles, the platform ensures that sensitive customer information remains confidential, utilizing cryptography and secure hardware to protect data throughout the process.
Privacy-First Analytics
Syntheticr 2.0 includes multiple banking entities, allowing the Amlytic platform to demonstrate capabilities in a multi-bank environment and detect criminal patterns across silos without sharing sensitive data.
Multi-Bank Collaboration
With the support of Syntheticr 2.0, FutureFlow and Secretarium successfully tested Amlytic across a multi-bank environment. One notable test involved simulating banks that initially struggled to detect suspicious activity in isolation.
However, once connected through Amlytic, they uncovered a network of over a million accounts within the synthetic dataset, showcasing the platform’s ability to scale and identify complex financial crime patterns effectively.
Futureflow and Secretarium subsequently won a prestigious G20 award, having proven how Amlytic could enhance multi-bank anti-money laundering (AML) efforts while remaining compliant with strict privacy regulations.
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