Exposure analytics
Sector, geography, currency, issuer, asset and strategy views.
DATA, RISK & PERFORMANCE
Risk analytics grounded in governed portfolio data.
Produce agreed exposure, concentration, scenario and risk views from governed portfolio data, with transparent assumptions, methodology, lineage and review status.
Overview
Risk analytics transforms portfolio positions, valuations, market data and approved methods into views used to understand exposure and risk. Depending on strategy, measures can include concentration, leverage, liquidity, factor exposure, scenario/stress tests, VaR or asset-specific credit/market metrics.
Most relevant to hedge funds, asset managers, multi-managers and sophisticated family offices; private-credit/real-asset strategies may use more asset-specific measures.
Our capabilities
Concentration / limits
Monitor approved concentration and limit thresholds against the governed exposure dataset.
Scenario / stress support
Run defined shocks and scenarios using approved assumptions and portfolio populations.
Risk metrics
Calculate agreed measures using validated methodology.
Risk reporting
Deliver recurring risk dashboards and packs with transparent data and methodology.
Data/control support
Reconcile analytics population to controlled portfolio data.
Service coverage
Core records
- Validated positions
- Market/pricing data
- Security/reference data
- Risk factor/model inputs
- Fund guidelines/limits
- Approved methodology
Operating activities
| Step | Activity | What happens |
|---|---|---|
| 1 | Reconcile portfolio | Confirm analytics population. |
| 2 | Classify | Map exposures and risk attributes. |
| 3 | Calculate | Apply approved methodology. |
| 4 | Validate | Run reasonableness/movement tests. |
| 5 | Review exceptions | Investigate limit or data issues. |
| 6 | Publish | Release risk view with assumptions/lineage. |
Reporting and oversight
- Exposure dashboard
- Concentration report
- Limit monitoring
- Scenario/stress outputs
- Risk metric report
- Exception/methodology notes
What clients gain
Clear exposure views
Sector, geography, currency, issuer, asset and strategy views.
Stronger concentration monitoring
Monitor approved concentration and limit thresholds against the governed exposure dataset.
Consistent scenario analysis
Run defined shocks and scenarios using approved assumptions and portfolio populations.
Transparent risk metrics
Calculate agreed measures using validated methodology.
Governance and integration
Risk Analytics is delivered through defined responsibilities, controlled records and documented review. Material exceptions, judgements and approvals remain visible and attributable throughout the operating process.
- Use approved/reconciled positions.
- Model/methodology version control.
- Separate limit breaches from data-quality issues.
- No unvalidated AI-generated risk model.
- Clear decision-support—not investment advice—language.
Expertise and delivery
Experts behind the service.
Relevant professionals support service design, exception review and delivery governance where specialist judgement is required.
Meet our Experts & ProfessionalsTechnology that supports control.
Controlled data, workflow and review capabilities support consistent execution, transparent oversight and traceable evidence.
Explore Technology & ExpertiseConfigured around your operating model.
Services can be delivered through managed operations, technology enablement, co-sourced delivery or transition support.
See How We WorkFrequently asked questions
Which risk measures should be listed?
Only measures Kelton can genuinely support; market examples include exposures, VaR, stress and factor analytics.
Does this replace a CRO/risk manager?
No. It supports data and analytics while formal risk oversight remains with responsible professionals.
Why connect risk to operations?
Using the same reconciled positions reduces conflicting numbers across risk, accounting and operations.
Discuss Risk Analytics
Start with one workflow, one operating issue or one provider transition. We will map the current process, responsibility boundaries, required data and a practical first engagement.