Collaborative Profiling is one of the advanced techniques in our fraud models for prepaid card fraud

New FICO data shows high rate of card fraud as criminals hitch a ride on Uber and Lyft

Artificial Intelligence is encountering new demands in the areas of responsibility, advocacy and regulation.

Credit cards appear to be the main target of fraud, with an average fraud rate 1.5 times that of debit cards

As both creditors and third-party debt servicers change their operating models, economic challenges and regulations will prove harder to manage

FICO analytics can identify more low-value card fraud, an important next step in stopping criminals

The BoE's new report says explainable AI is necessary for machine learning to be applied in credit management

As CNP fraud targets the online growth in luxury spending, new analytics improve the velocity of detection

However efficient and advanced a debt collection operation is, it’s being stress-tested by a multitude of factors in ways not seen since the last global recession.

When we look at how card issuers are dealing with three key factors — the performance of delinquent credit card portfoli...

“I’m Scott Zoldi and I’ve authored 95 patents on AI, machine learning and various analytic techniques. I’m Chief Analytics Officer of FICO. Ask me Anything.*

Neural networks are a powerful form of machine learning, but their black box nature often defies explainability. We have found a solution to this problem.

Regarding fraud analytics for open banking, unsupervised machine learning can be a strong weapon for fighting financial crime events

Here’s my advice for 2019 in a nutshell: With IFRS 9 impacts and €780 billion of NPL in Europe alone, stop reading about AI and start thinking about optimization.

My recent patent work has laid a foundation for what I predict will be the tech industry’s biggest development in 2019: ethical AI.