AI, Data & Intelligence
ClearOne’s AI, Data & Intelligence practice transforms operational information into strategic foresight. We design, build, and manage data and intelligence frameworks that improve transparency, prediction, and performance across post-trade, treasury, risk, and finance. Our teams blend data engineering, advanced analytics, and responsible AI to convert complexity into clarity, giving leadership real-time insights into how their enterprise performs, adapts, and improves. AI is not seen as an experiment; it’s integrated into the operational fabric, measurable, auditable, and accountable. Client value: unified data truth, predictive control, and evidence-based decision confidence.
Intelligence built into the operational fabric
Institutional systems produce enormous amounts of data, but true intelligence only surfaces when that data is organized, understandable, and actionable. The AI, Data & Intelligence practice creates a managed foundation for data collection, validation, and analytics across all post-trade and enterprise functions. We help organizations monitor their operations in real time, identifying patterns, exceptions, and opportunities before they show up in reports.
Our experts cover capital markets, enterprise data management, and applied AI. They create architectures that integrate legacy and cloud systems, establish canonical data models, and incorporate controls that ensure every dataset is trusted, traceable, and regulator-ready. From reconciliation metrics to predictive risk analytics, our goal is to help institutions measure what matters and anticipate what’s next.
What institutions can expect
Data integrity
Consistent definitions, verified lineage, and reconciled datasets across systems.
Operational visibility
Live dashboards display volumes, exceptions, and cycle times in real time.
Predictive analytics
AI models that forecast settlement disruptions, liquidity issues, and capacity constraints.
Regulatory readiness
Audit trails and evidential data aligned with CAT, EMIR, MiFID II, SFTR, and other global mandates.
Automated insight
Machine agents that observe process behavior and identify anomalies before they turn into incidents.
Continuous learning
Closed feedback loops that utilize historical data to improve processes and decision-making logic.
From data engineering to explainable AI
Our AI, Data & Intelligence practice merges engineering expertise with applied science, blending human judgment, automation, and explainable algorithms into a single control framework.
- Data Architecture & Engineering – enterprise data design, ETL pipelines, streaming integrations, and cloud migration.
- Data Quality & Governance – lineage, stewardship, and golden-source frameworks aligned with BCBS 239, SOC 2, and ISO 27001.
- Applied AI & Machine Learning – supervised and unsupervised models for predictive analytics, anomaly detection, and operational optimization.
- Operational Analytics – dashboards, service metrics, and executive reports for operations, finance, and risk teams.
- AI Model Governance – validation, versioning, and explainability controls to ensure compliance with emerging AI assurance standards.
- Regulatory & Risk Intelligence – integrated analytics for transaction, exposure, and reporting data that support transparency and audit readiness.
Our specialists work at the crossroads of data, technology, and policy, ensuring every insight is clear, defensible, and aligned with the institution’s duty of care.
Assess → Unify → Activate → Institutionalize
Assess
Evaluate current data flows, quality, and control maturity; identify risks and redundancies.
Unify
Create a standard model that ensures data meaning is consistent across systems and jurisdictions.
Activate
Utilize analytics, automation, and AI to reveal predictive and prescriptive insights.
Institutionalize
Integrate governance, lineage tracking, and performance metrics into daily operations.
Each phase enhances transparency, accountability, and foresight, ensuring leadership decisions are guided by trusted, real-time evidence.
Operational ecosystem
AI, Data & Intelligence is designed to be platform-agnostic and interoperable. We integrate smoothly with client data warehouses, cloud platforms, and visualization systems. Our pipelines work across batch and streaming data, ensuring continuous validation and synchronization between front-, middle-, and back-office systems. AI models and analytics are fully explainable and traceable, complying with model risk and regulatory standards.
For clients moving toward autonomous operations, we offer proprietary accelerators for:
- AI-powered exception detection and resolution
- Predictive workload management
- Real-time forecasting of risk and performance
- Automated reporting validation and reconciliation processes
Every tool is provided within a governance-first framework, ensuring automation supports rather than obscures institutional control.
Questions teams often ask
No. We unify and extend them. Our role is to build a consistent, governed foundation beneath existing data and intelligence investments.
All models incorporate version control, feature traceability, and interpretability metrics. Governance dashboards offer transparency for risk and compliance teams.
Yes. Our pipelines can deliver validated, auditable data to regulatory reporting engines and risk systems.
We evaluate tangible improvements in data quality, operational predictability, and decision-making speed, turning insights into long-term institutional performance.
Talk with a ProServe advisor
In modern markets, intelligence is the foundation. ClearOne ProServe’s AI, Data & Intelligence practice develops the frameworks that enable organizations to see, understand, and manage themselves accurately. Talk to a ProServe advisor to learn how we can unify your data, implement AI effectively, and provide measurable insights that enhance control and speed up performance.