Infrastructure costs include high-performance servers, GPUs, cloud services, AI frameworks like TensorFlow or PyTorch, and data processing tools. Development costs cover salaries for data scientists, AI engineers, and developers. Data costs involve collecting quality datasets and investing in data warehousing and management systems. Operational costs encompass regular updates, bug fixes, customer support, and troubleshooting services.  Be ready for a significant time investment, too, as it is what AI for FinTech is notoriously known for.