Machine learning is a procedure that enables a computer to learn from data how to perform a certain task. Once a computer learns the task to a sufficient level, human experts are no longer needed.

Despite all of the safeguards and fraud detection systems in place, Capital One failed to monitor or detect the unauthorized activity.

One of machine learning’s most well-known use cases is fraud detection, an area that has drawn the attention of a growing number of technology suppliers looking to develop the best algorithms ...

Bespoke fraud ML models are powered by algorithms that learn from historical data, picking up on behaviors and characteristics commonly associated with fraud.

Featurespace’s advanced fraud management systems, that utilise deep machine learning and adaptive behavioural analytics, understand the ‘good’ behaviour of each customer more accurately and ...

Adyen debuts machine learning fraud detection tool Adyen (AMS: ADYEN), the global payments platform of choice for many of the world's leading companies, today launched Score. 5 31 August 2021 Be ...

How have AI and machine learning improved fraud detection in the fintech industry? What specific applications does this technology touch, and what mechanisms complement it?

By Etop Ekanem Amid high-level fraud in financial institutions and in organisations today, a Compliance Expert, Ewere Igbenigun, has harped on the need for financial institutions and other ...

Machine learning can prove ideal for anomaly detection throughout the company network. Here are three key scenarios where this can be put to good use “Prevention is the daughter of intelligence,” said ...

Interested in understanding how AI and machine learning are being used to prevent bot-based fraud attempts, I attended a few recent webinars with Kount's 3 Key Elements Needed For Successful Bot ...