New book explains how AI and machine learning are transforming banking through fraud detection, credit risk modeling, ...

Banks should take a page from the health sciences' playbook and use artificial intelligence to "nudge" consumers away from transactions that have the characteristics of known fraud schemes, writes ...

One of the most immediate risks is malicious exploitation. Criminal networks are already experimenting with AI tools capable of automating phishing campaigns, generating deepfake identities, and ...

Fraud detection already relies heavily on non-financial signals such as IP address, device fingerprinting, geolocation and behavioural biometrics. When linked with AML monitoring, these signals become ...

Fraud detection is no longer enough to protect today’s financial ecosystem. As digital transactions increase in volume and complexity, banks require intelligent systems that can assess risk with ...

Although AI has introduced a new threat in the world of payments fraud, it has also emerged as the analytical backbone of next-generation fraud mitigation systems.

Thailand is making significant strides toward becoming a cashless society, driven by advancements in digital payment systems, government initiatives, and consumer behaviours. While the rise of a ...

From Detection To Intelligence: how digital finance is reshaping fraud risk and compliance through behavioural insights, ...

AI has changed the rules of deception. What once took a skilled fraudster hours or days now takes a model seconds. Just in time for International Fraud Awareness Week 2025, 16-22 November 2025, a new ...

Fraud detection requires leveraging new tools and models to keep ahead of increasingly sophisticated fraud. Financial institutions use AI to detect and prevent billions of dollars of fraud each year ...