Learn how AI fraud detection protects iGaming platforms from bonus abuse, account takeovers, payment fraud, and AML risks.

The AI-driven fraud analytics framework operates across multiple areas to identify suspicious patterns in real time.

From fraud detection to back-office automation and payments optimisation to enhancing credit risk and underwriting, here’s ...

Explore PPDAI Group fintech operations, digital lending platform, AI-driven credit technology, consumer finance services, ...

Banks and e-wallets may use AI to help make decisions, but the central bank says they must use 'well-prepared and ...

For Canadian consumers, the message emerging from recent research is clear: artificial intelligence is becoming an important ...

Generative AI has transformed once-specialized attacks into assembly-line operations, including account takeovers (stealing ...

Artificial intelligence is rapidly reshaping how Nigerians shop, with nearly nine in 10 consumers now using AI-assisted tools ...

South Africa’s fraud detection tools struggle to keep pace as iGaming scams tripled in 2025 amid a shift to AI-based scams.

Abstract: Financial fraud detection systems confront the persistent challenge of concept drift, where fraudulent patterns evolve continuously to evade detection mechanisms. Traditional rule-based ...

From workflow automation agents to domain-specific AI copilots, Snowflake’s hackathon challenges developers to shape the next ...