Leaning Into Innovation to Bring Newfound Speed and Accuracy to Credit Risk Modelling

To really level-up decisioning, organizations need more data, more automation, more sophisticated processes, more forward-looking predictions and greater speed-to-decisioning. And to this end, they need AI, machine learning, and alternative data.

In an article in Global Banking & Finance Review, Kim Minor, Senior Vice President, Global Marketing at Provenir, outlines the key findings of a survey which reveal a great state of uncertainty in credit risk modelling, underscoring the need for AI, machine learning, and alternative data.

Read the full article at Global Banking & Finance Review.