Duco AI platform cuts post-trade reconciliation time 76%

Clients reported a 76% reduction in time spent on post-trade reconciliation after adopting Duco’s artificial intelligence platform, the company reported. The figure covers participating users that deployed the platform for post-trade matching and exception management.

Duco’s platform automates record matching across multiple data sources, identifies and classifies exceptions and applies machine learning that learns from prior resolutions to reduce repeat manual work. The company presented the outcome as an aggregate reported by customers rather than a uniform result for every client.

Firms described implementation steps that included connecting the platform to existing trade and reference data feeds, normalizing data formats and applying the platform’s matching rules and machine learning models. Users said that once integrations were complete the platform processed daily trade volumes and produced exception lists requiring fewer and shorter investigations.

Clients reported that improved automated matches and learned rules for recurring discrepancies reduced the volume of items needing human review. Duco attributed the time savings to faster matching and fewer manual interventions for reconciled trades.

Operational benefits reported alongside the time savings included faster exception triage and clearer visibility into recurring error types. Several firms reported they reallocated staff from routine reconciliation tasks to analytical or exception-focused roles. Duco noted the platform’s audit trail and automated documentation helped with internal reviews and external audits.

Market drivers for adopting automated reconciliation technology cited by participants included growth in trade volumes, increased complexity of post-trade workflows and pressure to reduce operational costs. Participating firms said they sought to reduce backlogs and improve throughput without proportionally increasing headcount.

Post-trade reconciliation is the process of ensuring trade records align across front-office, middle-office and back-office systems and with external counterparties. The work traditionally involves manual comparison of records, investigation of breaks and correction of mismatches; automation tools aim to speed matching, reduce exceptions and provide traceable workflows for investigations.

Duco emphasized that the 76% figure reflects reported time savings rather than a specific dollar value and that results vary by client, deployment scope and data quality.