The Client
Relying on FactSet as a primary source of market and reference data, this leading investment management firm ingests FactSet feeds across a range of instruments and data types to support investment analytics, portfolio management, and operational decision-making. The accuracy, completeness, and timeliness of these feeds directly influences the quality of investment decisions made across the business.
The Challenge
The firm’s reliance on FactSet data created a critical dependency on feed quality and reliability, one that its manual assurance approach was increasingly unable to satisfy at the speed and consistency required. Without automated controls, any degradation in feed quality or an undetected schema change could flow directly into investment analytics before anyone caught it.
-
Unreliable Feed Integration:
FactSet market and reference data required dependable integration into internal investment systems, but the existing integration approach lacked the robustness to guarantee completeness and accuracy.
-
Data-Quality Risk to Analytics:
Quality issues in inbound FactSet feeds risked propagating into investment analytics and decision-making, with limited automated controls to catch problems before they caused downstream impact.
-
Slow, Inconsistent Manual Checks:
Manual validation of inbound data was too slow to keep pace with feed volumes and too inconsistent to provide reliable assurance across all instruments and data types.
-
Schema Drift and Feed Change Risk:
Unmonitored changes to FactSet feed structures or schemas could break downstream processes unexpectedly, with no systematic mechanism to detect drift before it caused failures.
-
Limited Automated Assurance:
The absence of a continuous, automated assurance layer meant issues were regularly caught too late, after they had already affected data consumers.
The Impact
- 24/7 Automated QA monitoring.
- Zero Manual checks on inbound data.
- High Data quality on every feed.
The Solution
Hoonartek integrated FactSet feeds into the firm’s investment systems using Ab Initio DevFac pipelines, establishing a reliable, governed integration layer for all inbound market and reference data. An automated QA layer was built to validate every FactSet feed for completeness, accuracy, and timeliness, replacing the manual checks that had previously introduced inconsistency and delay into the assurance process.
Reconciliation and exception handling logic was implemented for inbound data, ensuring discrepancies are identified and routed for resolution before reaching downstream systems. Schema-drift and feed-change monitoring was introduced to detect structural changes in FactSet feeds and protect downstream processes from unexpected breakages. The DevFac automated test framework was applied for continuous data assurance, providing 24/7 QA coverage across all integrated feeds.
Key Benefits
-
High Data Quality:
Automated QA validates every FactSet feed for completeness, accuracy, and timeliness, ensuring only clean, trusted data reaches investment analytics and decision-making.
-
Reliable Feeds:
Reconciliation and continuous monitoring eliminate feed surprises, giving the firm confidence that inbound data is always consistent and complete.
-
Faster Assurance:
Automated controls replace manual checks entirely, delivering faster and more consistent validation across all instruments and data types.
-
Protected Downstream Processes:
Schema-drift monitoring detects and flags FactSet feed changes before they can break downstream systems, removing a persistent source of operational risk.
-
Continuous Coverage:
24/7 automated QA monitoring ensures that feed-quality issues are caught and acted on immediately, regardless of when they occur.