Meeder Public Funds Scales Government Reporting and Transparency with Clearwater
Meeder selected Clearwater as its investment accounting and reporting platform based on three core strengths.
Client Story
Client Story
Freeing the quants: how a US market utility moved from maintaining plumbing to modeling risk
Beacon by Clearwater gives the quantitative team at the center of the US financial markets a
production-grade platform for developing rates and fixed-income risk and analytics
The challenge
Our large US clearing house customer’s quantitative team was responsible for market analytics and risk oversight, and to provide the data to deliver insights from the clearinghouse’s unique point of view to regulators, clearing members, and the market at large.
But the team ran on a custom-built development and production stack. Quants spent too much time maintaining the plumbing, from database upgrades to integrations to infrastructure, and not enough time innovating. A highly skilled quant team was acting like an expensive IT support function. In addition, their custom tech stack did not scale adequately to support their computational requirements and ran on expensive in-house servers.
The stakes of getting risk wrong are different for a clearinghouse. A hedge fund asks how much it might lose. A CCP asks how much a member could lose, and therefore fail to pay, before positions can be closed out. VaR feeds margin calculation, default management, liquidity planning, stress testing, and regulatory frameworks. Underestimating it can exhaust collateral and put confidence in settlement at risk.
The solution
The customer selected Beacon as its new quantitative development and production platform, replacing the in-house stack. Beacon runs as a SaaS instance on AWS, so the team gets a modern, scalable environment without owning the infrastructure beneath it.
Today the team of roughly 50 quants uses Beacon to build and run rates and fixed-income risk models, including curves, valuations, VaR, and sensitivities. Market and position data flows in directly from the customer’s Snowflake warehouse, and results are delivered to the customer’s own cloud storage and downstream systems.
What the quants are building
- Curves
Treasury curves (bootstrapping, custom discount curves, and spline fitting), SOFR curves, and Fed Funds curves built around FOMC meeting dates.
- Instruments
Treasuries and T-bills, TIPS, agency bonds, floating-rate notes, repo (including standalone financing legs), MBS/TBA, Treasury futures (cheapest-to-deliver, basis, implied repo), SOFR futures with convexity adjustment, Fed Funds futures, swap futures, and interest rate swaps.
- Risk analytics
Portfolio VaR with simulated book-level P&L and attribution, rho and theta reports, partial durations, a year of daily sensitivity history, and analysis of how SOFR fixings move the curve.
- Clearing and guarantee fund calculations
Dedicated code to support clearing fund analytics.
- Regulatory and market views
The customer’s position in the ecosystem gives it a unique view to model counterparty risk in equities and MBS for regulatory reporting.
Data, integration and operations
- Snowflake
Beacon connects over private networking with key-pair authentication, replacing manual file loading for market and position data.
- Scheduled snapshots and delivery
A midday market and position snapshot feeds intraday runs, with results pushed to the customer’s own storage.
- Enterprise fit
Integrates with the customer’s alerting, security monitoring, IP management, CI/CD pipelines, observability tooling, and single sign-on with an approval-based release process.
- Resilience
Production runs with cross-region failover across AWS regions, reviewed through the customer’s architecture governance.
The value
| What changed | What it means for the CCP |
|---|---|
| Quants back on quant work | Database upgrades, hardware, and warehouse integration are handled by the Beacon support team, so the quants’ time shifts from plumbing to models and insight. Platform upgrades are delivered on a CI/CD model providing a constant stream of enhancements while avoiding the heavy lift associated with version upgrades associated with legacy risk platforms. |
| Risk at production scale | Complex calculations run over very large datasets on elastic cloud compute, without a hardware build-out. Beacon dynamically scales as workloads increase and gives back compute resources when they are no longer required. |
| Intraday risk views | VaR calculations delivered to risk teams multiple times a day, and to research teams twice a day, across thousands of data points. |
| Proprietary models, fully owned | The CCP builds and deploys models tailored to its own IP rather than a vendor’s prescribed methodology. |
| Clearing-grade assurance | Passed a rigorous vendor risk and application security review; production runs with cross-region failover. |
| Faster path to new analytics | New reports and risk views can be developed on the platform with expert support from Clearwater. |
Why it matters beyond one team: when quants spend their time on models instead of maintenance, the CCP can respond faster to new risk questions from clearing members, regulators, and the media, and can explain the numbers behind its answers.
Why Beacon
Beacon is built for the way CCP quant teams actually work, and it differs from legacy risk systems:
- Your models, along with Beacon’s
Beacon provides an extensive set of financial models and risk applications. Clients can lever Beacon’s code or create and deploy their own risk models tailored to your IP instead of a legacy vendor’s closed models.
- Native financial intelligence
A financial object hierarchy with built-in understanding of complex instruments, so teams build and iterate faster.
- Transparent and traceable
Open source code lets teams see and explain every input to a model or calculation.
- Fast by design
A dependency graph data model links every data point so all relevant data flows into high-speed calculations, backed by elastic compute that scales up and down with demand.
- A real development environment
An integrated environment for building, QA/testing, and deploying, with Jupyter notebooks for data science teams.
- Cloud-native and secure
Architected for the cloud from day one, with bank-grade security and global redundant infrastructure.
- Expert partnership
Experienced professional services teams and quant developers help customers make the most of the platform.