Investment performance attribution
Teams report different performance contributions because classifications and calculation inputs drift.
The challenge behind the workflow.
Teams report different performance contributions because classifications and calculation inputs drift.
Connect trades, positions, prices, reference data, and client reporting with consistent timestamps and definitions. Help operations, risk, and finance review discrepancies using reproducible analytical inputs and explicit approval boundaries.
Data to bring together
- Portfolio returns
- Benchmark data
- Instrument classifications
Source systems are examples of the data required. Confirm connector availability, permitted access, refresh timing, and the authoritative owner before implementation.
How Genedata supports the work.
Configure one connected workflow, then reuse its mappings, definitions, and review process as the business grows.
- 01
Connect and prepare
Agree calculation periods and align approved portfolio and benchmark references.
Build the preparation as a reusable visual workflow or reviewed code, with explicit source mappings and validation checks. - 02
Investigate and validate
Reconcile totals and compare contributions using documented attribution assumptions.
Keep shared definitions and source versions with the analysis so another team can reproduce the result. - 03
Publish and review
Deliver a reproducible analytical pack with source versions and definitions.
Make the output available to the right people with appropriate access, ownership, and review evidence.
A performance attribution evidence pack
Make the next run easier.
Reusable attribution inputs reduce manual reconstruction during reporting reviews.
Start from one approved example. Save the agreed mappings and definitions, publish the reviewed output, and let the next team follow the same evidence instead of rebuilding the preparation.
Measure your own improvement
Time to reproduce a performance attribution result
Record a baseline before the pilot and compare like-for-like work afterward. Results depend on source quality, configuration, and adoption.Review and responsibility
Qualified professionals validate methodology and client-facing interpretations.
AI with professional judgment.
Use AI to explain data differences and draft investigation notes. Investment, valuation, trade, and compliance decisions remain with authorized professionals.
Try the workflow with your team.
Use representative, approved sample data. Agree the expected output and a review owner before extending the workflow to a live process.