Electronic trading is accelerating, and with it the number of trading venues continues to swell, from DLT-based platforms to crypto exchanges. While this proliferation represents progress for the industry, it carries a hidden danger: banks risk fines or losses simply because they missed a change to a venue’s rulebook or capabilities.
Over the past six months, Corlytics has met with more than 15 global banks across New York and London. The findings are stark. The largest institutions now trade across hundreds of venues, with some exceeding a thousand, yet none have dedicated tooling to monitor how those rulebooks evolve. In most cases, the responsibility falls to a single junior analyst armed with little more than a spreadsheet.
RegTech firm Corlytics recently talked about the elephant in the trading room nobody is pricing.
For business heads, this represents both a control gap and a constraint on growth. Firms cannot expand electronic trading or safely adopt new venues and capabilities while remaining blind to the rules governing them. Ambition, in other words, meets a wall of invisible rules.
The exposure is tangible and growing. Missing a change to an order type, a market-making obligation or a surveillance requirement carries consequences that are far from hypothetical. Fines and PnL hits can be substantial, as can the opportunity cost of electronification projects stalled by rules that no one can trust.
Perhaps most concerning is that this remains an unknown unknown. Few institutions have quantified the risk because they have never measured it, and what cannot be seen cannot be priced. The root cause lies in the absence of any industry standard: no machine-readable rules, no common language for venue rules and no automated engine to track them.
RegTech firm Corlytics has built a solution to address this gap. The company has converted millions of pages of unstructured rulebooks into structured, proprietary data, using an ensemble of models in which only 3% of the work is data extraction, with the remainder devoted to quality assurance to ensure the output can be trusted. The system rests on models refined over five years, €2.5m of R&D investment, 98% model accuracy and model governance built in from the outset, all backed by SLAs guaranteeing data delivery.
The result is a network in which venues are normalised and benchmarked, each venue’s core capabilities are mapped to a firm’s obligations, and every change is surfaced in real time. Rebuilding such infrastructure internally would be slow, costly and duplicative, whereas joining the network mutualises both the work and the cost.
The message for the industry is clear: banks that see every venue clearly will scale electronic trading safely, while those that stay blind remain one missed change away from a fine or a missed market.
Read the full Corlytics post here.
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