Application Fraud: The Role of AI and Machine Learning
I spoke with one of FICO’s principal scientists, Derek Dempsey, who shared how AI and machine learning are solving problems in application fraud.
4 Success Factors for Machine Learning in Fraud Detection
Machine learning in fraud detection performs better when we know the strengths and limitations of different analytic toolkits, and understand the factors that determine accuracy.
How Machine Learning Fights "Hypnofraud"
Hypnofraud refers to the success fraudsters are having with convincing people to give them their account data - but the fraud based on this can be detected and stopped.
Video: Addressing the Rise in Application Fraud
As a result of the rise in application fraud due to EMV adoption in the US, Citi is exploring new authentication protocols and new analytics.
Decision Management Maturity: Raise Yours at FICO World
The DM3 provides an accurate and actionable segmentation of users and businesses against their current capabilities, requirements, skills and end-state objectives.
Machine Learning Improves CNP Fraud Detection Rates by 30%*
FICO’s new machine learning models are much more sensitive to abnormal single transactions, allowing CNP fraud to be detected quickly.
Origination Scores: Say “Yes” to More Credit Applicants
Origination scores add significant value above and beyond the FICO® Score, which is based solely on the data found in a consumer’s credit bureau file.
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.
Unsupervised Learning Part 2: The AML Connection
Today’s post covers three categories of unsupervised learning that FICO has investigated, refined and put into our anti-money laundering (AML) solutions.
E-Commerce Fraud: Machine Learning Speeds Detection
FICO's new CNP fraud detection models have been developed to detect fraudulent e-commerce fraud transactions as quickly as possible, to prevent significant fraud loss from an account.
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?
Today’s Deep Dive: Innovative Unsupervised Learning in AI
This two-part blog unpacks the mysteries of two very different AI techniques: supervised and unsupervised learning.
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.
IoT: Will Your Car Let You Drive Home from the Bar?
In my new post on TechTarget's IoT Agenda, I explore how behavioral analytics could change driving for the better.
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