Amlytic is a secure, large scale multi-party transaction data pooling tool for financial institutions. Detecting money laundering patterns in support of fighting financial crime.

Amlytic accounts

Amlytic | Alerts

Amlytic rooms

Winning tech

A-Team Innovation Awards 2021
Most innovative financial data security solution
Most innovative use of DLT

Part of DANIE

Danie logo

A community of financial institutions harnessing the latest Privacy-Enhancing Technology (PET) to collaborate and share insights securely, without having to rely on a trusted third party.

Data control

Each party keeps control of their own data

No ties to others

No ties to other participants

Easy to use

Easy to use, no IT skills required


Scales to support billions of transactions

Providing large-scale transaction analytics

Collaboration between multiple financial institutions is essential to provide efficient anti-money laundering (AML) and counter-terrorist financing (CFT). But sensitivity of data and regulation prevents actors from pooling data together in clear text.

Scalable to billions of transactions, Amlytic is built on Secretarium's privacy-preserving technology protecting sensitive data, and leverages FutureFlow's large-scale graph analysis to automatically spot irregular relationship patterns and correlations indicative of malicious activity.

Amlytic screenshot
Identifies patterns

Identifies patterns of suspicious behaviour

Improvement in key metrics

Pooling demonstrated up to 8x improvement in key metrics

Machine learning

Unsupervised machine learning

Global architecture

Secretarium provides the privacy layers of Amlytic through an encrypted Secure Multi-Party Pseudonymisation (SMPP) engine that securely matches and de-duplicates financial institutions contributions using fuzzy logic. The SMPP engine then uses a hardware secret to generate a fully de-identified pooled dataset.

FutureFlow leverages grid computing to run unique analytics on the de-identified data. The generated networks of transactions are then analysed with artificial intelligence.

Financial institutions are then notified with their original data from the SMPP engine and can leverage Secretarium's Secure Rooms to collaborate, ultimately being able to invite Financial Investigation Units.

Global architecture diagram


Data is securely contributed to Secretarium for matching and de-identification


De-identified and pooled data is then contributed to FutureFlow for analytics


Analytical output is available for proactive and on-demand analysis by financial institutions