Can AI Transform Cash Cycle Management?

Every part of the cash cycle generates data that could improve policy and operations. The challenge is accessing that data, standardising it, and turning it into decisions. AI does not remove the need for human judgement, but it can make fragmented cash-cycle data more visible, comparable, and useful.

A Giesecke+Devrient Spotlight paper describes AI as an 'orchestration layer' across the cash cycle: a way to improve forecasting, inventory management and operations while leaving final decisions with experienced people.

Although the article focuses on central banks, the same logic applies to retailers, commercial banks, cash-in-transit (CIT) companies, and cash management firms. They hold much of the operational data that would make AI-driven analysis more accurate and more valuable.

G+D sets out four scenarios where AI could make a practical difference.