In a series on TechTarget's IoT Agenda, I discuss the 3 E's of artificial intelligence: ethical, explainable, and efficient.

In practical applications with impactful consequences, we need reliable, explainable models with well-defined scores that generalize well on yet-unseen data.

By leveraging machine learning, the FICO Falcon can help to capture the latest scams and frauds.

New processes and tools are needed to deal with an escalating number of customers with payment challenges

In today's fully digital environment, it's more important than ever to improve identity verification and validation processes for customer onboarding and management

In this deep dive, Scott Zoldi explains how innovations in machine learning and self-calibrating models are finding more fraud and reducing false positives

Data bias and untrained data scientists pose risks to AI models - and the trust we place in business decisions

Helping health authorities and governments with access to CDRs or facilitating digital communications could help containment

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.

From financial inclusion to AI failures, here are four things I see happening

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

Subscription fraud is growing, while use of AI and machine learning remains surprisingly low

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