How does progress in artificial intelligence stack up to the FICO credit score model?

Blending artificial intelligence, machine learning and domain expertise in the design of credit scores - a video discussion with Agus Sudjianto

Naomi Palmer, a fraud consultant at FICO, won silver in the ‘Team Player of the Year’ category

Financial services partner organizations should offer best-in-class customer communication technology, with easy implementation, ongoing management and impressive results

Multi-channel vs. omni-channel communications may seem to be a matter of semantics, but it represents a real difference in how successful your customer programs will be

A new survey shows how many debt collectors are missing the mark in their contact strategies

The pandemic has put stress on lenders' and debt collectors' ability to meet inbound demand - here are 5 points for reviewing your abilities

New data points to problems lenders have executing customer-centric collections

The UK's financial regulator is calling for greater operational resilience - here's how collections operations can respond

Taking a forward-looking approach to debt management can help us manage the current crisis

FICO Scores R&D has empirically investigated potential benefits and risks associated with using some of the latest AI and machine learning approaches for credit scoring.

My presentation on “Transparency by Design: An Explainable AI Approach to Credit Risk Scoring” discusses our application of recent machine learning technologies to challenge the US FICO® Score.

The National Board for Customer Disputes in Sweden have ruled that banks should be liable for so-called “push payment” fraud losses over a certain amount.

Counterfeit cards are relatively simple to spot. So how were the criminals in the European road tolls scheme successful?

How are advances in artificial intelligence and machine learning changing credit risk assessment? That’s a topic I’ll be exploring in three presentations at FICO World 2018.