Duco
AI data reconciliation platform for financial services that automates matching and exception management at scale.
What it does
Duco is an AI-native data reconciliation platform used by banks, asset managers, brokers, and financial data firms to automate the matching and reconciliation of financial data - trade confirmations, position records, cash movements, NAV calculations, and regulatory reporting data. Its AI capabilities include intelligent matching rules that learn from historical reconciliation patterns to automatically match records across counterparty and internal data sources, anomaly detection that flags data quality issues and exceptions requiring investigation, AI-powered exception prioritization that routes the most time-sensitive and highest-risk breaks for immediate resolution, and reconciliation analytics that identify recurring discrepancy patterns indicating systematic data or process issues.
Why AI-NATIVE
Duco is AI-native - machine learning matching that learns organizational reconciliation patterns and AI exception prioritization from financial data characteristics are the core product capabilities rather than rule-based matching enhanced with analytics.
Best for
Mid-market banks, asset managers, and brokers use Duco for automated financial data reconciliation - AI matching reducing the manual effort of daily trade, position, and cash reconciliation processes.
Large financial institutions use Duco for enterprise-scale reconciliation - AI handling millions of matching decisions daily across complex multi-counterparty data environments and exception analytics identifying systemic data quality problems.
Limitations
Duco is purpose-built for financial data reconciliation — non-financial services organizations needing general-purpose data matching find other data quality tools more appropriate.
Duco's value depends on connecting to trading systems, custodians, and counterparty data sources — organizations with many legacy or non-standard data sources face integration complexity before AI reconciliation can operate.
Getting optimal AI matching performance requires configuring matching rules and tolerances aligned with business requirements — this requires experienced reconciliation operations expertise, not just technical implementation.
Alternatives by segment
| If you need… | Consider instead |
|---|---|
| Financial close automation | BlackLine |
| Enterprise data quality platform | Informatica |
| Trade reconciliation specialist | Smartstream |
Duco pricing not published. Financial services contracts based on data volume, number of reconciliations, and user count. Annual contracts. Enterprise pricing negotiated.
