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

A price elasticity model enables the product team to set deposit rates with a sound understanding of the expected performance from the rate strategy

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

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.

What should you expect to gain from deposit price elasticity models and what can you do with them to maximize benefit to the business?

Want to know which consumers will more likely default when they encounter an unpredicted financial stress situation in the future? Traditional risk scores won’t give you the full picture.