These best practices can help you not just meet regulators’ requirements but also increase the value your models add to the business

Here is useful information on how to assess alternative data and combine it with so-called traditional data to improve credit risk analytics

With the right technology it is now possible to drive out manual or high-friction interventions and offer seamless, near-instant credit decisions across multiple sales channels

Understand what fraud analytics entail and how they leverage AI, machine learning, business intelligence and data science to improve fraud detection

FICO® Focused Language Model and FICO® Focused Sequence Model set global standards for Responsible AI, delivering measurable enterprise value

A unified decisioning platform enforces development standards to ensure AI systems are built responsibly from the ground up

Which works better for building credit risk models: using AI and machine learning or using traditional scorecards?

Here's how to get the full power of machine learning without losing the transparency that’s important from credit risk scorecards

This FICO World presentation highlights the vital importance of balancing customer care with collections success in a highly regulated environment

GenAI hallucinations are primarily caused by the ways that large language models (LLMs) are built

We have built a data science organization that prizes creativity and operationalizes innovation for demonstrable business benefit and positive customer impact

Ethical AI means digging into what machine learning models are learning – which is a complex task

As companies drive breakthrough results with AI in 2025, operationalization and trust are attainable imperatives

FICO’s use of blockchain to develop artificial intelligence is recognized in awards from Global Finance and the Banking Tech Awards

Responsible AI includes four principles for ensuring that AI is safe, trustworthy and unbiased - it should be robust, explainable, ethical and auditable