1956 was a momentous year in statistical scoring and credit decisioning: 1) Bill Fair and Earl Isaac founded Fair Isaac & Co., which launched the FICO Score in the US, and 2) the formal field of artificial intelligence (AI) is generally considered to have been created at the Dartmouth Workshop on Artificial Intelligence. Since then, credit data and analytic methods evolved from descriptive analytics to prescriptive analytics (see Figure 1). Now, 70 years later, these two watershed events have come together with the advent of AI/ML, large language models (LLMs), generative AI (GenAI), and agentic AI.

This new era of AI-driven analytics is transforming how financial institutions originate loans, evaluate credit, fraud, and pricing risk. The opportunities are great but the choices, costs, ROI, TCO, and risks of adopting alternative data, AI/ML, GenAI, and agentic AI analytic methods requires a technology roadmap.

The opportunities are great and this analysis helps FIs:

1. Identify How AI Will Drive Faster Adoption of New Data Sources
2. How to Integrate AI into Lending Processes and Systems
3. Utilize Modern Lending Platforms for Workflow and Integration
4. Map the AI Vendor Ecosystem to Select the Right Partner