Preventing Application Fraud with Machine Learning and AI
When it comes to application fraud, machine learning analytics must be a critical part of a financial institution’s control strategy.
Best Practices in Fraud Management: Q&A with Bob Shiflet
How is application fraud evolving? And what should fraud leaders be doing to manage fraud risk in a digitally connected world?
What Data Do I Need to Fight Application Fraud?
It’s raining data left and right, and you need to start by understanding what data you already have to fight application fraud and where there are gaps.
ELI5: How Does the Dark Web Work?
When we talk about brute force application fraud and bot-net attacks, what are we really talking about?
Morris Dancing, the Bubonic Plague and IFRS 9
IFRS 9 changes the accounting recognition of loan impairment from an “incurred” to an “expected” loss basis, requiring new predictive models that bring the worlds of accounting and credit risk modelling ever closer together.
Application Fraud — Establishing Your Fraud Risk Appetite
Fraud and security are a top priority for financial institutions — but just stopping fraud isn’t enough. Managing fraud is a balancing act that starts with knowing your fraud risk appetite.
Application Fraud – From Identity Theft to First-Party Fraud
Identity theft, also known as third-party fraud losses, is just the tip of the application fraud iceberg. First-party fraud can be 10 times as much.
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