Workflow Wednesdays is a live online session series from Tokenovate that examines one real post-trade problem each month, in twenty minutes. Webinars run every three weeks, on Wednesdays, starting with solving the dilemma of data fragmentation.
We believe the industry is missing a recurring online event that discusses the ongoing workflow challenges of the post-trade industry, and a place where industry professionals would be able to ask questions and get answers to problems they may face.
The Industry Talks About Post-Trade in the Abstract
Post-trade operations carry a category of cost that rarely gets discussed publicly: reconciliation breaks chased down by hand, regulatory reports rebuilt because the automated version doesn’t match what’s expected, settlement instructions caught and corrected at the last minute. Each issue is treated as an isolated routine task. But combined, they are a structural cost many firms have learned to live with, even as T+1 timelines compress the room for error and CSDR penalties raise the price of getting it wrong.
Industry conversation about post-trade tends to stay at the level of regulation and market structure: the October 2027 T+1 deadline, CSDR cash penalties, the shift toward tokenised settlement. All real, all worth tracking. The operational reality underneath those headlines, however, rarely gets the same airtime: what actually happens on a desk when a trade fails to match, or a report has to be pulled together from three different sources against a deadline.
Tokenovate’s Workflow Wednesdays series was created to spend time at that level: one industry problem per session, explained properly and with a solution.
What Workflow Wednesdays Actually Is
Each Workflow Wednesdays session takes one real post-trade problem, the kind of thing that quietly eats into an operations team’s week, and works through how it gets solved.
Sessions are twenty minutes. That length is deliberate because we feel it is long enough to explain the mechanics of a challenge and solution properly, and short enough that a post-trade operations lead can attend between meetings without clearing an hour from their calendar. There’s no product pitch and no generic panel discussion. Just the problem, the mechanics behind it, and what solving it looks like in practice.
First Up: Reconciliation Overhead From Data Fragmentation
The first session will be about the mechanics: how a trade’s data ends up looking different across five or six separate systems, and what it takes to catch that before it becomes a reconciliation break. Our recent piece on post-trade data normalisation goes deeper into the same mechanics for anyone who wants a head start. Gartner puts the average cost of poor data quality at $12.9 million per organisation per year, and the longer a mismatch goes uncaught, the more expensive it gets to fix.
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