Usecases
Danske Bank prevents card fraud with the use …
Danske Bank has leveraged machine learning technology to fight fraud across all its payment channels. Featurespace's ARIC Fraud Hub prevents fraud by detecting anomalies in a user's behavioural profile, in real time. The bank is mitigating the risk while also eliminating false positives to offer greater customer experience.
Toronto-Dominion(TD) Bank plans to offer personalised recommendations for …
TD Bank acquires Layer 6 to predict customer needs and offer personalised products using its deep learning platform. According to Layer 6, the platform is one of the best in coming up with recommendations for new users (cold start).
Revolut reduces bank card fraud using machine learning …
Revolut, the online-based challenger bank, has recently introduced machine learning as a way to detect fraudulent e-commerce activity and card theft/fraud using machine learning.
The European Central Bank identifies vulnerabilities at individual, …
The European Central Bank (ECB) has been using Silo.AI's Bank Early Warning Model (BEWM) since 2014 to identify potential bank distress. The machine learning model has been trained to monitor signs and causes of financial stability of banks at both the country and Eurozone level. The model is useful to the ECB to make more informed decisions and avoid future …
Clearbank combats fraud and money laundering with the …
ClearBank has deployed machine learning technology to fight fraud and optimise its anti-money laundering (AML) operations. The U.K's new clearing bank is using Featurespace's ARIC™ platform that develops individual behavioural profiles and detects abnormal activity in real time, using machine learning.
NatWest Bank prevents over £7m worth of corporate …
NatWest has partnered with Vocalink Analytics to create and deploy a fraud detection system which works by analysing historic payment data to spot new potentially fraudulent payments. The system focuses on invoice payment redirection, which it claims has avoided making over £7M in fraudulent payments.