Even with significant investment in data and technology, data quality and governance challenges threaten to undermine strategic AI ambitions for Payments and Fintech firms in the year ahead, according to a new report from data and analytics firm Dun & Bradstreet. 

More than half of Payments (54%) and Fintech (51%) firms state that AI projects have failed as a result of poor data. 

Despite these setbacks, AI and technology remain key focus areas. In the year ahead, Payments firms are looking to prioritise customer-facing AI innovation (38%) and the internal use of AI (35%), while Fintech firms will prioritise digital transformation and investment in technology and data (42%), and the internal use of AI (38%).

Adding complexity to the data landscape are pervasive issues like distrust in data sets (Payments: 52%, Fintech: 57%), duplicate data (Payments: 55%, Fintech: 58%), and siloed or disparate data systems (Payments: 54%, Fintech: 47%). These foundational problems directly hinder firms' ability to leverage data effectively. Just a third (Payments: 32%, Fintech: 39%) currently feel able to make informed business decisions with their data. 

“As companies increasingly look to adopt AI and unlock benefits, this report makes one thing clear: effective AI cannot be achieved without the foundation of AI-ready data. Without that, even the most advanced technology will fall short.” says Sara de la Torre, Head of Banking, Financial Services and Insurance at Dun & Bradstreet UK&I