Series 35 - The Critique: Dismantling the Month-End Close With AI

The argument that AI agents will dismantle the month-end close is compelling in principle and frequently misunderstood in practice. The misunderstanding is almost always the same: organisations interpret "dismantling the close" as "making the close faster" — deploying AI to automate the manual tasks within the close process, reducing the time from ten days to five days, from five days to three. This is process optimisation, not close elimination, and it preserves the fundamental architecture that makes the close necessary. A faster close is still a close. The organisation is still accumulating incomplete positions during the month and resolving them at month-end. The calendar dependency has not been eliminated — it has been compressed.
Dismantling the close with AI requires a different intervention: eliminating the conditions that make the close necessary, rather than automating the tasks that the close requires. This means deploying AI agents at the points in the financial workflow where incompleteness accumulates. The first point is the reconciliation workflow: most organisations accumulate hundreds or thousands of unreconciled items during the month because the reconciliation process is manual and is therefore batched — run weekly or monthly rather than continuously. An AI reconciliation agent that runs every time a transaction posts eliminates the accumulation. The second point is the accrual workflow: most organisations estimate accruals at month-end because the information needed to calculate them precisely — the delivery confirmations, the service completion certificates, the vendor invoices — arrives asynchronously and is not tracked continuously. An AI accrual agent that monitors the event stream and calculates accruals from confirmed events rather than estimates eliminates the estimation requirement. The third point is the intercompany workflow: most organisations spend a significant proportion of their close effort resolving intercompany mismatches that arose during the month from timing differences, currency movements, and posting inconsistencies. An AI intercompany agent that monitors both sides of every intercompany relationship continuously and resolves mismatches in real time eliminates the month-end resolution batch.
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About the Host
Rıdvan Yiğit is the Founder & CEO of RTC Suite — the world's first Autonomous Compliance and Payment Intelligence platform, built natively on SAP BTP and operating across 80+ countries.
Connect with Rıdvan:
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ridvan.yigit@rtcsuite.com
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Видео Series 35 - The Critique: Dismantling the Month-End Close With AI канала Ridvan Yigit