In a global study conducted with 400 decision makers in fintech and financial services organizations, we uncovered a high degree of uncertainty in credit risk modeling accuracy and a growing appetite for AI predictive analytics and machine learning, data integration and the use of alternative data.

Listen in as Robin Amlôt of IBS Intelligence, and Carol Hamilton, SVP Global Solutions at Provenir, discuss the findings revealed in this research and how organizations plan to use data, AI, and decisioning to improve credit risk decisioning and support the key imperatives of fraud detection/prevention and financial inclusion.