Anomaly detection is one of the more difficult and underserved operational areas in the asset-servicing sector of financial institutions. Broadly speaking, a true anomaly is one that deviates from the ...

Abstract: Fraud in supply chain operations poses significant risks to businesses, including financial losses, operational inefficiencies, and erosion of stakeholder trust. With the increasing ...

Anomaly detection in the context of data science is detecting a data sample that is out of the ordinary and does not fit into the general data pattern (or an outlier). This deviation can result from a ...

Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow Despite the success of supervised machine learning and deep ...

In recent years, machine learning (ML) algorithms have proved themselves to be remarkably useful in helping people deal with different tasks: data classification and clustering, pattern revealing, ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More At the advent of the modern AI era, when it was discovered that powerful ...

Artificial intelligence and machine learning aren’t just fictional pieces of futuristic Hollywood movies. Power plants can deploy these innovative technologies today to more accurately predict the ...

Before Covid-19 financial institutions saw a 10:1 ratio of bot-based malicious to legitimate login attempts, according to Aite Group's Fraud & AML practice. Malicious login attempts are setting new ...