# How Do Regulators Expect Firms to Govern and Backtest Their Use of the ISDA SIMM? ▴ Question

**Published:** 2025-08-14
**Categories:** Question

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## Concept

Regulatory authorities mandate a rigorous and transparent governance structure for any firm utilizing the ISDA Standard [Initial Margin](https://prime.greeks.live/area/initial-margin/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) Model (SIMM). This expectation extends beyond mere calculation of initial margin; it demands a comprehensive framework that substantiates the model’s fitness for purpose on an ongoing basis. The core principle is that SIMM, while a standardized methodology, is not a “set and forget” utility. Firms bear the ultimate responsibility for ensuring the model adequately covers their specific [counterparty risk](https://prime.greeks.live/area/counterparty-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) profiles at the required 99% confidence level, a task that necessitates a dynamic and responsive governance and backtesting apparatus.

The system of oversight regulators envision is one of active management rather than passive reliance on the global ISDA governance process. While ISDA coordinates industry-wide development, validation, and recalibration of the SIMM, individual firms are expected to implement their own robust, internal frameworks for portfolio monitoring and the remediation of any identified shortfalls. This dual responsibility creates a system of checks and balances.

ISDA manages the global standard, but the firm is accountable for the local application. Regulators have explicitly voiced concerns about firms over-relying on the ISDA-level governance and failing to adequately challenge and supplement the model when their specific portfolio risks diverge from the assumptions underpinning the standard model.

At its heart, the regulatory expectation is a mandate for a culture of empirical skepticism. A firm must be able to demonstrate, with data, that it continuously validates the SIMM’s outputs against its actual risk exposures. This involves a detailed process of [backtesting](https://prime.greeks.live/area/backtesting/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), identifying exceptions, and, most importantly, acting on those exceptions through a clear and bilaterally agreed-upon remediation process, such as the application of [margin add-ons](https://prime.greeks.live/area/margin-add-ons/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). The framework is designed to ensure that the standardized model does not become a systemic vulnerability, particularly during periods of market stress or when applied to portfolios with unique risk characteristics, such as those of many hedge funds.

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## Strategy

A firm’s strategic approach to SIMM governance and backtesting must be built upon two foundational pillars ▴ a comprehensive internal [governance framework](https://prime.greeks.live/question/how-does-centralized-governance-differ-from-a-federated-data-governance-model/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) and a robust, multi-faceted backtesting program. These elements are interconnected, with the outputs of the backtesting program serving as critical inputs that inform and validate the governance process. The objective is to create a closed-loop system that perpetually monitors, identifies, and remediates [model performance](https://prime.greeks.live/question/can-superior-counterparty-performance-quantification-directly-translate-to-measurably-improved-fund-performance/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) issues.

> A successful strategy treats SIMM not as a static calculation engine, but as a dynamic risk model requiring constant validation and potential augmentation.

![Intersecting concrete structures symbolize the robust Market Microstructure underpinning Institutional Grade Digital Asset Derivatives. Dynamic spheres represent Liquidity Pools and Implied Volatility](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-framework-optimizing-rfq-execution-and-liquidity-for-principal-trading.jpg)

## The Governance Mandate

Developing a compliant governance framework requires a firm to move beyond simple operational procedures and establish clear lines of accountability and oversight. Regulators expect a structure that is both transparent and effective, ensuring that model performance is not just a quantitative exercise but a central component of risk management dialogue.

Key components of this framework include:

- **Model Ownership** ▴ Designating a specific senior executive or committee responsible for the firm’s use of SIMM. This individual or group is accountable for the model’s performance, governance, and interaction with regulators.

- **Independent Review** ▴ Establishing a function, independent of the primary risk-taking units, to periodically review and challenge the firm’s SIMM process. This includes validating the backtesting methodology, assessing the appropriateness of data sources, and ensuring remediation procedures are followed.

- **Change Management Protocol** ▴ Implementing a formal process for managing updates to the SIMM, whether driven by ISDA’s annual or off-cycle recalibrations or by internal decisions to apply specific add-ons. This protocol must document the rationale for any changes and their expected impact.

- **Remediation Policy** ▴ A detailed policy outlining the specific steps to be taken when a [backtesting exception](https://prime.greeks.live/question/how-does-the-intermarket-sweep-order-exception-practically-work-during-a-block-trade/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) or model shortfall is identified. This policy must define what constitutes a material shortfall, the process for negotiating and applying margin add-ons with counterparties, and the escalation path for reporting persistent issues to ISDA.

![A solid object, symbolizing Principal execution via RFQ protocol, intersects a translucent counterpart representing algorithmic price discovery and institutional liquidity. This dynamic within a digital asset derivatives sphere depicts optimized market microstructure, ensuring high-fidelity execution and atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-microstructure-orchestration.jpg)

## The Backtesting Imperative

Backtesting is the empirical core of the SIMM validation strategy. Regulators have expressed concerns about over-reliance on certain standard backtesting methodologies, such as the “3+1” approach, which can be limited by its use of in-sample data and its failure to account for non-modelled [risk factors](https://prime.greeks.live/area/risk-factors/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). A sophisticated strategy, therefore, incorporates multiple backtesting approaches to create a more holistic view of model performance.

A comparative look at different backtesting philosophies reveals their distinct roles:

| Backtesting Approach | Primary Function | Key Advantage | Regulatory Consideration |
| --- | --- | --- | --- |
| Historical Backtesting (e.g. 3+1) | Meets baseline ISDA requirement for performance monitoring. | Standardized and comparable across the industry. | Viewed as a necessary but potentially insufficient metric due to in-sample data overlap. |
| Hypothetical P&L Backtesting | Isolates model performance by using a static portfolio. | Removes the “noise” of daily trading activity to purely test the model’s risk factor sensitivities. | Provides a clean assessment of the core calibration. |
| Actual P&L Backtesting | Tests the model against realized gains and losses. | Offers the most realistic view of how the model performed against real-world market movements and portfolio changes. | Considered a crucial test of the model’s effectiveness in a live environment. |
| Dynamic Backtesting | Identifies which specific risk factors or products are driving exceptions. | Provides actionable intelligence for targeted remediation, such as specific product add-ons. | Demonstrates a proactive and granular approach to risk management. |

By integrating these different backtesting methods, a firm can construct a narrative of model performance that is far more compelling to a regulator. It demonstrates an understanding of the model’s limitations and a proactive stance toward identifying and mitigating potential shortfalls before they become material issues.

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## Execution

The execution of a regulatory-compliant SIMM framework translates the strategic principles of governance and backtesting into a series of defined, operational, and auditable processes. This is where the theoretical structure meets the practical realities of data management, quantitative analysis, and bilateral counterparty negotiation. Regulators expect firms to not only define these processes but also to produce tangible evidence of their consistent application.

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## Operationalizing the Backtesting Cycle

The backtesting cycle is a continuous operational process, not a periodic event. It involves a disciplined flow of data collection, calculation, analysis, and reporting. A firm must be able to demonstrate its capability to execute this cycle with precision and timeliness.

The core steps in an operational backtesting workflow are:

- **Data Aggregation** ▴ Daily collection of all required data, including end-of-day positions for each in-scope portfolio, market data for all relevant SIMM risk factors, and the calculated SIMM value for that day.

- **P&L Calculation** ▴ Computation of the one-day change in portfolio value (the actual P&L). This requires the same clean, validated market data used for risk calculations to ensure a consistent comparison.

- **Exception Identification** ▴ A daily comparison of the actual P&L against the collected SIMM. An exception occurs when the loss on the portfolio exceeds the initial margin held.

- **Threshold Monitoring** ▴ Applying the agreed-upon monitoring thresholds to filter out noise. Exceptions that breach these thresholds are flagged for further investigation. This is a critical step to focus resources on material events.

- **Root Cause Analysis** ▴ For every material exception, a deep-dive analysis is performed. This is where Dynamic Backtesting becomes essential, allowing the firm to attribute the shortfall to specific trades, risk factors, or market events.

- **Reporting and Escalation** ▴ Documenting the findings and escalating them through the governance structure. This includes internal management reporting and, where required, reporting data to ISDA to inform its industry-wide monitoring.

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## The Remediation Playbook

Identifying a model shortfall is only the first step. The critical execution component is remediation. Regulators scrutinize a firm’s ability to act on its findings. This requires a clear playbook for addressing identified issues, both bilaterally with counterparties and through engagement with the broader ISDA governance process.

> A documented backtesting exception without a corresponding documented remediation action is a significant red flag for regulators.

The table below outlines a typical remediation process following a significant backtesting exception, illustrating the expected actions and outputs.

| Phase | Action | Key Stakeholders | Expected Output / Evidence |
| --- | --- | --- | --- |
| Identification | A backtesting exception exceeds the internal reporting threshold. | Risk Analytics Team, Model Validation | A documented exception report detailing the date, portfolio, shortfall amount, and market context. |
| Analysis | Perform dynamic backtesting to identify the root cause (e.g. a specific commodity volatility risk not captured). | Risk Analytics Team, Quantitative Analysts | An analytical report attributing the shortfall to specific risk factors or products. |
| Internal Governance | Present findings to the Model Oversight Committee. | Head of Market Risk, Committee Members | Meeting minutes documenting the committee’s review and decision on next steps. |
| Bilateral Engagement | Contact the counterparty to present the findings and propose a margin add-on. | Collateral Management, Counterparty Relationship Manager | Formal communication records (emails, call logs) and a bilaterally agreed-upon add-on amount or multiplier. |
| Implementation | Apply the agreed-upon add-on to the daily margin calculation for the specific counterparty portfolio. | Collateral Operations, IT | System logs showing the application of the add-on; updated margin call reports. |
| Industry Reporting | Submit anonymized shortfall data to ISDA as per the governance framework requirements. | Regulatory Reporting Team | Confirmation of data submission to ISDA. |

This structured execution provides a clear audit trail that demonstrates to regulators that the firm’s governance framework is not merely a document, but a living process that actively manages and mitigates model risk. The ability to produce this evidence on demand is the ultimate validation of the firm’s adherence to regulatory expectations.

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## References

- ISDA. (2022, July 15). ISDA SIMM®,1 GOVERNANCE FRAMEWORK. International Swaps and Derivatives Association.

- Smith, Stuart. (2023, August 30). How governance changes in the SIMM model impact firms. Futures & Options World.

- Acadia. (n.d.). Improving the Initial Margin Model. Retrieved from Acadia website.

- Bank of England Prudential Regulation Authority. (2022, June 28). PRA’s review of the use of the SIMM model ▴ Conclusions.

- ISDA. (2024, September 19). ISDA Publishes ISDA SIMM® Methodology, Version 2.7. International Swaps and Derivatives Association.

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## Reflection

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## From Compliance to Systemic Resilience

The intricate web of governance and backtesting requirements surrounding the [ISDA SIMM](https://prime.greeks.live/area/isda-simm/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) prompts a fundamental question for any financial institution. Is the firm’s risk architecture designed merely to satisfy a regulatory checklist, or is it engineered for genuine resilience? The mandated processes ▴ the monitoring, the exception analysis, the remediation protocols ▴ provide the raw materials for a far more potent system. They offer a continuous, data-driven feedback loop on a portfolio’s true economic risk.

Viewing this framework as a strategic asset, rather than a compliance burden, shifts the entire operational perspective. The ultimate objective transcends regulatory approval; it becomes the construction of an anticipatory risk management function, capable of identifying and neutralizing model weaknesses before they manifest as critical, uncollateralized losses in a stressed market. How does your firm’s current execution of these mandates contribute to that higher-order goal?

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## Glossary

<a href="https://prime.greeks.live/area/counterparty-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Counterparty Risk

Meaning ▴ Counterparty risk denotes the potential for financial loss stemming from a counterparty's failure to fulfill its contractual obligations in a transaction. </a><a href="https://prime.greeks.live/area/initial-margin/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Initial Margin

Meaning ▴ Initial Margin is the collateral required by a clearing house or broker from a counterparty to open and maintain a derivatives position. </a><a href="https://prime.greeks.live/area/margin-add-ons/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstract geometric structure with sharp angles and translucent planes, symbolizing institutional digital asset derivatives market microstructure. The central point signifies a core RFQ protocol engine, enabling precise price discovery and liquidity aggregation for multi-leg options strategies, crucial for high-fidelity execution and capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/principals-operational-framework-optimizing-institutional-digital-asset-derivatives-rfq-protocol-execution-for-alpha-generation.jpg)

## Margin Add-Ons

Meaning ▴ Margin Add-Ons represent specific, dynamically applied surcharges or adjustments to base margin requirements within institutional digital asset derivatives frameworks, designed to account for granular, real-time risk factors that extend beyond standard collateralization methodologies. </a><a href="https://prime.greeks.live/area/backtesting/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Intersecting metallic components symbolize an institutional RFQ Protocol framework. This system enables High-Fidelity Execution and Atomic Settlement for Digital Asset Derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-system-specialists.jpg)

## Backtesting

Meaning ▴ Backtesting is the application of a trading strategy to historical market data to assess its hypothetical performance under past conditions. </a><a href="https://prime.greeks.live/question/how-does-centralized-governance-differ-from-a-federated-data-governance-model/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Two smooth, teal spheres, representing institutional liquidity pools, precisely balance a metallic object, symbolizing a block trade executed via RFQ protocol. This depicts high-fidelity execution, optimizing price discovery and capital efficiency within a Principal's operational framework for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-bridging-institutional-liquidity-pools-via-rfq-protocol-for-optimized-digital-asset-derivatives-price-discovery.jpg)

## Governance Framework

Centralized governance enforces universal data control; federated governance distributes execution to empower domain-specific agility. </a><a href="https://prime.greeks.live/question/can-superior-counterparty-performance-quantification-directly-translate-to-measurably-improved-fund-performance/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Angular metallic structures precisely intersect translucent teal planes against a dark backdrop. This embodies an institutional-grade Digital Asset Derivatives platform's market microstructure, signifying high-fidelity execution via RFQ protocols](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-high-fidelity-execution-system-architecture.jpg)

## Model Performance

Quantifying counterparty execution quality translates directly to fund performance by minimizing costs and preserving alpha. </a><a href="https://prime.greeks.live/question/how-does-the-intermarket-sweep-order-exception-practically-work-during-a-block-trade/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Two spheres balance on a fragmented structure against split dark and light backgrounds. This models institutional digital asset derivatives RFQ protocols, depicting market microstructure, price discovery, and liquidity aggregation](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-price-discovery-liquidity-aggregation.jpg)

## Backtesting Exception

The Intermarket Sweep Order enables rapid block execution by simultaneously clearing superior-priced quotes on other venues. </a><a href="https://prime.greeks.live/area/risk-factors/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Risk Factors

Meaning ▴ Risk factors represent identifiable and quantifiable systemic or idiosyncratic variables that can materially impact the performance, valuation, or operational integrity of institutional digital asset derivatives portfolios and their underlying infrastructure, necessitating their rigorous identification and ongoing measurement within a comprehensive risk framework. </a><a href="https://prime.greeks.live/area/isda-simm/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Translucent, overlapping geometric shapes symbolize dynamic liquidity aggregation within an institutional grade RFQ protocol. Central elements represent the execution management system's focal point for precise price discovery and atomic settlement of multi-leg spread digital asset derivatives, revealing complex market microstructure](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-driving-optimal-liquidity-aggregation-for-precise-price-discovery-and-atomic-settlement.jpg)

## Isda Simm

Meaning ▴ ISDA SIMM, the Standard Initial Margin Model, represents a standardized, risk-sensitive methodology for calculating initial margin requirements for non-centrally cleared derivatives transactions. </a>

**Tags:** [Risk Factor](https://options.greeks.live/area/risk-factor/), [Non-Cleared Derivatives](https://options.greeks.live/area/non-cleared-derivatives/), [Backtesting](https://options.greeks.live/area/backtesting/), [Regulatory Compliance](https://options.greeks.live/area/regulatory-compliance/), [Model Governance](https://options.greeks.live/area/model-governance/), [Counterparty Risk](https://options.greeks.live/area/counterparty-risk/)	

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Initial margin secures potential future risk at a trade's outset; variation margin settles current daily market fluctuations.

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The close-out period's length directly scales risk, determining the time horizon for loss potential and thus the total initial margin.

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Machine learning improves counterparty classification by transforming static risk assessment into a dynamic, predictive, and data-driven system.

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### [What Are the Primary Differences between Initial Margin and Variation Margin?](https://options.greeks.live/question/what-are-the-primary-differences-between-initial-margin-and-variation-margin/)
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Initial Margin is a forward-looking collateral buffer against potential default; Variation Margin is a real-time settlement of current market value changes.

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SIMM recalibration mandates an evolution from reactive compliance to a proactive, systemic architecture for managing long-term capital and operational risk.

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The ISDA SIMM model transforms margin into a quantifiable cost, forcing portfolio construction to optimize for both market risk and capital efficiency.

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Initial Margin and Variation Margin systematically mitigate CVA by collateralizing potential future and current exposures, respectively.

- 
### [How Does the Adoption of ISDA SIMM for Bilateral Trades Influence a Firm’s Overall Risk Management Strategy?](https://options.greeks.live/question/how-does-the-adoption-of-isda-simm-for-bilateral-trades-influence-a-firms-overall-risk-management-strategy/)
![A sleek, futuristic object with a glowing line and intricate metallic core, symbolizing a Prime RFQ for institutional digital asset derivatives. It represents a sophisticated RFQ protocol engine enabling high-fidelity execution, liquidity aggregation, atomic settlement, and capital efficiency for multi-leg spreads.](https://options.greeks.live/wp-content/uploads/2025/07/advanced-institutional-digital-asset-derivatives-rfq-protocol-execution-engine-for-optimal-liquidity-aggregation-and-atomic-settlement.jpg)

Adopting ISDA SIMM transforms initial margin from a disputed operational burden into a transparent, optimizable component of risk strategy.

- 
### [How Does Collateralization Differ between Liquid and Illiquid RFQ Trades?](https://options.greeks.live/question/how-does-collateralization-differ-between-liquid-and-illiquid-rfq-trades/)
![A central split circular mechanism, half teal with liquid droplets, intersects four reflective angular planes. This abstractly depicts an institutional RFQ protocol for digital asset options, enabling principal-led liquidity provision and block trade execution with high-fidelity price discovery within a low-latency market microstructure, ensuring capital efficiency and atomic settlement.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-rfq-protocol-core-system-for-high-fidelity-execution-and-aggregated-liquidity.jpg)

Collateralization evolves from an automated, market-priced process for liquid trades to a negotiated, model-based protocol for illiquid ones.

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---

**Original URL:** https://options.greeks.live/question/how-do-regulators-expect-firms-to-govern-and-backtest-their-use-of-the-isda-simm/
