# How Do Internal Models under Basel II and III Affect a Bank's Capital Requirements? ▴ Question

**Published:** 2025-08-02
**Categories:** Question

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## Concept

The decision for a financial institution to employ [internal models](https://prime.greeks.live/area/internal-models/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) for capital adequacy calculations is a fundamental architectural choice. It represents a deliberate move from a standardized, one-size-fits-all regulatory blueprint to a bespoke, high-fidelity system engineered to reflect the bank’s unique risk profile. This transition is predicated on a core principle ▴ a bank’s own internal [risk management systems](https://prime.greeks.live/area/risk-management-systems/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), when sufficiently robust, can provide a more precise and risk-sensitive measure of potential losses than a generalized formula created by regulators.

The effect on [capital requirements](https://prime.greeks.live/area/capital-requirements/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) is a direct consequence of this precision. By capturing the specific nuances of its portfolio ▴ the granular correlations, the specific hedging strategies, the actual diversification benefits ▴ a bank can often justify holding a lower amount of regulatory capital compared to the amount mandated by the [standardized approach](https://prime.greeks.live/area/standardized-approach/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).

The Basel II framework was the first to systemically codify this principle on a global scale. It operated on the premise that empowering banks to use their own approved models would foster more sophisticated [risk management](https://prime.greeks.live/area/risk-management/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) practices throughout the industry. The framework acted as an incentive. Institutions that invested in the data infrastructure, quantitative talent, and governance protocols necessary to build and validate these models were rewarded with greater [capital efficiency](https://prime.greeks.live/area/capital-efficiency/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite).

The [internal models approach](https://prime.greeks.live/area/internal-models-approach/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (IMA) allowed banks to use their proprietary data to estimate key risk parameters like [Probability of Default](https://prime.greeks.live/area/probability-of-default/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (PD) and Loss Given Default (LGD) for their credit exposures, or to use advanced statistical methods like Value-at-Risk (VaR) for market risk. The direct outcome was that risk-weighted assets (RWAs), the denominator in capital ratio calculations, could be calibrated more accurately to the bank’s actual risk-taking activities.

> A bank’s adoption of internal models fundamentally shifts its capital calculation from a generic regulatory template to a customized measure of its specific risk architecture.

[Basel III](https://prime.greeks.live/area/basel-iii/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), however, emerged from the crucible of the 2007-2008 financial crisis, which revealed significant flaws in the implementation and oversight of these models. The subsequent regulations introduced a more skeptical and rigorous architectural overlay. The core concept of allowing internal models remained, but it was fortified with stringent validation requirements and crucial backstops. The system’s architecture was upgraded with enhanced security protocols.

The transition marked a shift in regulatory philosophy, acknowledging that the flexibility granted by Basel II required a much stronger supervisory and quantitative framework to prevent gaming and ensure the stability of the entire financial system. The effect on capital requirements became more complex; while the potential for capital efficiency through IMA persisted, it was now bounded by a much more demanding set of operational and analytical proofs.

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## What Is the Core Difference in Approaches?

The primary distinction between the standardized approach and the internal [models approach](https://prime.greeks.live/question/what-are-the-strategic-trade-offs-between-the-standardised-approach-and-the-internal-model-approach-under-frtb/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) lies in the source and granularity of [risk parameters](https://prime.greeks.live/area/risk-parameters/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). The standardized approach is a top-down, regulator-defined methodology. Supervisors prescribe specific risk weights for various asset classes. For instance, a corporate loan might be assigned a 100% risk weight, while a residential mortgage might receive a 35% weight.

These weights are intentionally broad and conservative, designed to apply universally to all banks regardless of their individual risk management sophistication. It is a system built for simplicity and comparability.

The internal models approach is a bottom-up, bank-specific methodology. Under this framework, a bank leverages its own historical data and predictive models to estimate the risk parameters for its unique portfolio. Instead of using a prescribed [risk weight](https://prime.greeks.live/area/risk-weight/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), the bank calculates the probability of a borrower defaulting and the potential loss if that default occurs. This allows for a much more nuanced differentiation of risk.

Two corporate loans that would receive the same 100% risk weight under the standardized approach could have vastly different capital implications under IMA if one is to a highly-rated, stable utility company and the other is to a volatile startup. The IMA is engineered for risk sensitivity, rewarding institutions that can demonstrably manage and measure their risks with greater precision.

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## Strategy

The strategic decision to adopt an internal models approach under the Basel frameworks is a commitment to transforming a bank’s risk management function from a compliance-driven cost center into a strategic asset capable of optimizing capital allocation. The strategy [under Basel](https://prime.greeks.live/question/how-does-the-net-to-gross-ratio-impact-the-potential-future-exposure-calculation-under-the-basel-framework/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) II was largely focused on achieving capital arbitrage. Banks invested heavily in quantitative modeling capabilities with the explicit goal of demonstrating to regulators that their internal risk assessments were more accurate than the standardized tables, thereby lowering their RWA calculations and, consequently, their minimum capital requirements.

This freed up capital that could be deployed for lending and other revenue-generating activities, directly impacting profitability. The strategic objective was clear ▴ build a model that is both compliant and efficient.

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## The Strategic Evolution from Basel II to Basel III

The strategic landscape shifted dramatically with the implementation of Basel III. The financial crisis demonstrated that some banks’ internal models were inadequately calibrated, particularly for tail events, and that the pursuit of capital efficiency had, in some cases, led to an underestimation of systemic risk. Basel III introduced a new strategic calculus. The focus moved from pure capital optimization to a more balanced objective of demonstrating robust model governance and performance under stress.

The introduction of stricter validation protocols, such as the Profit & Loss (P&L) attribution test and more rigorous backtesting, meant that the models had to perform accurately on an ongoing basis. A model that looked good on paper but failed to explain the bank’s actual daily trading profits and losses would be disqualified.

Furthermore, Basel III introduced a critical new component ▴ the [output floor](https://prime.greeks.live/area/output-floor/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). This mechanism sets a lower limit on the capital benefits a bank can derive from its internal models. Specifically, it mandates that a bank’s total RWA, as calculated by its internal models, cannot fall below a certain percentage (phased in to 72.5%) of the RWA calculated using the standardized approach. This strategic buffer was designed to reduce the variability in RWA calculations across banks and to ensure a minimum level of capital adequacy across the system, acting as a global safeguard against excessive model-driven capital reduction.

> Basel III recalibrated the internal models strategy, demanding that the pursuit of capital efficiency be balanced with demonstrable model robustness and adherence to a system-wide capital floor.

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## Comparative Analysis of Model Frameworks

The strategic choice between the standardized and internal models approach involves a trade-off between operational simplicity and capital efficiency. The table below outlines the core differences from a strategic perspective.

| Attribute | Standardised Approach | Internal Models Approach (IMA) |
| --- | --- | --- |
| Risk Sensitivity | Low. Uses broad, regulator-defined risk buckets. | High. Utilizes bank-specific data and models for granular risk assessment. |
| Capital Implications | Generally higher capital requirements due to conservative, one-size-fits-all risk weights. | Potential for lower capital requirements by more accurately reflecting the portfolio’s risk profile, subject to the Basel III output floor. |
| Operational Complexity | Low. Relatively simple to implement and report. | Very High. Requires significant investment in data, technology, quantitative expertise, and ongoing model validation. |
| Supervisory Scrutiny | Standard compliance checks and audits. | Intense and continuous. Requires explicit supervisory approval for models and ongoing performance tests like P&L attribution. |

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## How Did Basel III Change Market Risk Models?

One of the most significant strategic shifts under Basel III was the overhaul of the internal models approach for [market risk](https://prime.greeks.live/area/market-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). Basel II relied on the Value-at-Risk (VaR) metric, which estimates the maximum potential loss over a specific time horizon at a given confidence level (e.g. 99%). While useful, VaR was criticized for its inability to capture the severity of losses beyond that confidence level ▴ the so-called “tail risk.” A VaR model could tell a bank it was unlikely to lose more than $100 million on a given day, but it said nothing about whether the loss, if it did occur, would be $101 million or $1 billion.

Basel III replaced VaR with the [Expected Shortfall](https://prime.greeks.live/area/expected-shortfall/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) (ES) methodology for calculating capital requirements. ES measures the average loss that would be incurred in the tail of the distribution, specifically when losses exceed the VaR threshold. It answers the question ▴ “If things go badly, what is the average of our worst-case losses?” This change forces banks to hold capital against the severity of extreme events, a direct response to the failures observed during the 2008 crisis. The strategic implication is that banks must now focus their modeling and hedging strategies on mitigating the magnitude of extreme losses, a more robust approach to risk management.

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## Execution

The execution of an internal models approach is a deeply technical and operationally intensive undertaking. It requires a bank to build and maintain a sophisticated infrastructure that is subject to rigorous and continuous [supervisory approval](https://prime.greeks.live/area/supervisory-approval/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite). The process moves beyond theoretical modeling into a granular, evidence-based demonstration of a model’s accuracy and the governance framework that supports it. A bank cannot simply choose to use its models; it must earn that right by meeting a stringent set of qualitative and quantitative standards set by its national supervisor. 

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## The Supervisory Approval Process

Gaining approval to use the IMA is a multi-stage process that forms the bedrock of the execution framework. It is designed to ensure that the bank’s risk management systems are conceptually sound, empirically validated, and integrated into its daily operations.

- 
**Initial Application and Documentation** ▴ The bank must submit a comprehensive application to its supervisory authority. This documentation details the model’s design, methodology, assumptions, and the underlying data used for its calibration. It must also describe the bank’s internal validation processes, the expertise of its quantitative teams, and the governance structure, including the roles of senior management and the internal audit function. 

- 
**Qualitative Standards Assessment** ▴ Supervisors evaluate the bank’s risk management culture and infrastructure. They assess whether the model is an integral part of the bank’s decision-making process. A model used solely for regulatory capital calculation while business decisions are made on other metrics would fail this test. The bank must demonstrate a robust internal control environment.

- 
**Quantitative Validation and Testing** ▴ This is the most demanding phase. The bank must provide extensive evidence that its model is accurate. This involves rigorous backtesting, where the model’s predictions are compared against actual outcomes over a historical period. Under Basel III, this also includes the Profit & Loss Attribution (PLA) test for [market risk models](https://prime.greeks.live/area/market-risk-models/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite), which ensures the [risk factors](https://prime.greeks.live/area/risk-factors/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite) in the model can explain the majority of the trading desk’s daily P&L. 

- 
**Live Testing and Monitoring** ▴ Before granting final approval, supervisors may require a period of live testing where the model runs in parallel with the standardized approach. This allows the regulator to monitor the model’s performance in real-time. Even after approval, the model is subject to continuous monitoring and periodic re-validation by both the bank and its supervisor.

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## Executing the Expected Shortfall Calculation

The core of the Basel III market risk IMA is the calculation of Expected Shortfall (ES). This is a complex statistical measure that must be computed daily for each trading desk using the IMA. The execution involves several key parameters mandated by the Basel framework.

- **Confidence Level** ▴ The ES must be calculated at a 97.5th percentile, one-tailed confidence level. This is a more conservative standard than the 99th percentile often used for VaR under Basel II. 

- **Stress Calibration** ▴ The ES calculation must be calibrated to a period of significant financial stress. The model must replicate the outcome that would occur on the bank’s current portfolio if the underlying risk factors experienced a shock equivalent to a historical crisis period (e.g. the 2008 crisis). This ensures the capital charge is sufficient to withstand severe market dislocations. 

- **Liquidity Horizons** ▴ The model must account for the fact that it may take time to exit or hedge a position in a stressed market. Basel III specifies different liquidity horizons for different categories of risk factors, which are then used to scale the ES calculation. 

The table below provides a simplified example of how risk factors are mapped to liquidity horizons, a critical step in the execution of the ES calculation.

| Risk Factor Category | Examples | Base Liquidity Horizon (Days) |
| --- | --- | --- |
| Interest Rate (Major Currencies) | USD, EUR, JPY government bond yields | 10 |
| Equity (Large Cap) | S&P 500, FTSE 100 constituents | 20 |
| Credit Spread (Investment Grade) | Spreads on A-rated corporate bonds | 40 |
| Commodities | Crude Oil, Gold | 60 |
| Exotic/Structured Products | Complex derivatives, securitized products | 120 |

This tiered liquidity horizon system means that positions in less liquid assets automatically attract a higher capital charge, as the model must simulate the risk of holding that position for a longer period under stressed conditions. The execution of the IMA under Basel III is a far more granular and demanding process, directly linking capital requirements to both the statistical properties of the portfolio and the practical realities of liquidating it in a crisis.

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## References

- Basel Committee on Banking Supervision. “MAR30 – Internal models approach ▴ general provisions.” Bank for International Settlements, 2023.

- Basel Committee on Banking Supervision. “MAR33 – Internal models approach ▴ capital requirements calculation.” Bank for International Settlements, 2023.

- Behn, Markus, et al. “The Bumpy Road to Risk-Weights-Based Capital Requirements.” Journal of Financial and Quantitative Analysis, vol. 56, no. 5, 2021, pp. 1773-1804.

- Tarullo, Daniel K. “Banking on Basel ▴ The Future of International Financial Regulation.” Peterson Institute for International Economics, 2008.

- Le Leslé, Vanessa, and Sofiya Avramova. “Revisiting Risk-Weighted Assets.” IMF Working Paper, WP/12/90, International Monetary Fund, 2012.

- Bank Policy Institute. “Internal Models Should Be Allowed for Credit Capital Requirements.” BPI, 16 Nov. 2023.

- Picardo, Elvis. “Basel III ▴ What It Is, Capital Requirements, and Implementation.” Investopedia, 29 May 2024.

- Capital.com. “What is an Internal Models Approach for Market Risk?” Capital.com, 26 Oct. 2022.

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## Reflection

The evolution from Basel II to Basel III reflects a maturation in the global understanding of financial risk. The frameworks governing internal models are not merely sets of compliance rules; they are complex operating systems designed to govern how a bank perceives and capitalizes its own risk. As you evaluate your institution’s own operational framework, consider the architecture of your risk intelligence. Is it built merely to satisfy a regulatory requirement, or is it a dynamic system that provides a genuine strategic edge?

The data, the models, and the governance protocols are the components of this system. The ultimate strength of the institution depends not on the individual components, but on their seamless integration into a coherent and resilient architecture capable of navigating both calm and turbulent market conditions.

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## Glossary

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

Meaning ▴ Risk Management Systems, within the intricate and high-stakes environment of crypto investing and institutional options trading, are sophisticated technological infrastructures designed to holistically identify, measure, monitor, and control the diverse financial and operational risks inherent in digital asset portfolios and trading activities. </a><a href="https://prime.greeks.live/area/internal-models/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Abstract depiction of an advanced institutional trading system, featuring a prominent sensor for real-time price discovery and an intelligence layer. Visible circuitry signifies algorithmic trading capabilities, low-latency execution, and robust FIX protocol integration for digital asset derivatives](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-prime-os-high-fidelity-rfq-protocols.jpg)

## Internal Models

Meaning ▴ Within the sophisticated systems architecture of institutional crypto trading and comprehensive risk management, Internal Models are proprietary computational frameworks developed and rigorously maintained by financial firms. </a><a href="https://prime.greeks.live/area/standardized-approach/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Standardized Approach

Meaning ▴ The Standardized Approach refers to a prescribed regulatory methodology used by financial institutions to calculate capital requirements or assess specific risk exposures. </a><a href="https://prime.greeks.live/area/capital-requirements/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Capital Requirements

Meaning ▴ Capital Requirements, within the architecture of crypto investing, represent the minimum mandated or operationally prudent amounts of financial resources, typically denominated in digital assets or stablecoins, that institutions and market participants must maintain. </a><a href="https://prime.greeks.live/area/capital-efficiency/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Capital Efficiency

Meaning ▴ Capital efficiency, in the context of crypto investing and institutional options trading, refers to the optimization of financial resources to maximize returns or achieve desired trading outcomes with the minimum amount of capital deployed. </a><a href="https://prime.greeks.live/area/risk-management/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Risk Management

Meaning ▴ Risk Management, within the cryptocurrency trading domain, encompasses the comprehensive process of identifying, assessing, monitoring, and mitigating the multifaceted financial, operational, and technological exposures inherent in digital asset markets. </a><a href="https://prime.greeks.live/area/internal-models-approach/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Internal Models Approach

Meaning ▴ The Internal Models Approach (IMA) describes a regulatory framework, primarily within traditional banking, that permits financial institutions to use their proprietary risk models to calculate regulatory capital requirements for market risk, operational risk, or credit risk. </a><a href="https://prime.greeks.live/area/probability-of-default/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Probability of Default

Meaning ▴ Probability of Default (PD) represents the likelihood that a borrower or counterparty will fail to meet its financial obligations within a specified timeframe. </a><a href="https://prime.greeks.live/area/basel-iii/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Basel Iii

Meaning ▴ Basel III represents a comprehensive international regulatory framework for banks, designed by the Basel Committee on Banking Supervision, aiming to enhance financial stability by strengthening capital requirements, stress testing, and liquidity standards. </a><a href="https://prime.greeks.live/question/what-are-the-strategic-trade-offs-between-the-standardised-approach-and-the-internal-model-approach-under-frtb/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
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## Models Approach

The choice between FRTB's Standardised and Internal Model approaches is a strategic trade-off between operational simplicity and capital efficiency. </a><a href="https://prime.greeks.live/area/risk-parameters/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![The image depicts two interconnected modular systems, one ivory and one teal, symbolizing robust institutional grade infrastructure for digital asset derivatives. Glowing internal components represent algorithmic trading engines and intelligence layers facilitating RFQ protocols for high-fidelity execution and atomic settlement of multi-leg spreads](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-platform-1.jpg)

## Risk Parameters

Meaning ▴ Risk Parameters, embedded within the sophisticated architecture of crypto investing and institutional options trading systems, are quantifiable variables and predefined thresholds that precisely define and meticulously control the level of risk exposure a trading entity or protocol is permitted to undertake. </a><a href="https://prime.greeks.live/area/risk-weight/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A sleek, bi-component digital asset derivatives engine reveals its intricate core, symbolizing an advanced RFQ protocol. This Prime RFQ component enables high-fidelity execution and optimal price discovery within complex market microstructure, managing latent liquidity for institutional operations](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-engine-optimal-execution.jpg)

## Risk Weight

Meaning ▴ Risk Weight represents a numerical factor assigned to an asset or exposure, directly reflecting its perceived level of inherent risk for the purpose of calculating capital adequacy. </a><a href="https://prime.greeks.live/question/how-does-the-net-to-gross-ratio-impact-the-potential-future-exposure-calculation-under-the-basel-framework/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A central, metallic, multi-bladed mechanism, symbolizing a core execution engine or RFQ hub, emits luminous teal data streams. These streams traverse through fragmented, transparent structures, representing dynamic market microstructure, high-fidelity price discovery, and liquidity aggregation](https://options.greeks.live/wp-content/uploads/2025/07/principal-grade-digital-asset-derivatives-rfq-protocol-engine-facilitating-high-fidelity-execution-and-optimal-price-discovery-across-fragmented-market-microstructure.jpg)

## Under Basel

The Net-to-Gross Ratio calibrates Potential Future Exposure by scaling it to the measured effectiveness of portfolio netting agreements. </a><a href="https://prime.greeks.live/area/output-floor/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![Precision-engineered modular components display a central control, data input panel, and numerical values on cylindrical elements. This signifies an institutional Prime RFQ for digital asset derivatives, enabling RFQ protocol aggregation, high-fidelity execution, algorithmic price discovery, and volatility surface calibration for portfolio margin](https://options.greeks.live/wp-content/uploads/2025/07/firm-fx-options-rfq-trade-system-key-microstructure-data-flow-core-engine.jpg)

## Output Floor

Meaning ▴ An Output Floor is a regulatory constraint, specifically within the Basel framework, that sets a minimum level for an institution's risk-weighted assets (RWA) calculations, irrespective of the results derived from internal risk models. </a><a href="https://prime.greeks.live/area/market-risk/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![An exposed institutional digital asset derivatives engine reveals its market microstructure. The polished disc represents a liquidity pool for price discovery](https://options.greeks.live/wp-content/uploads/2025/07/high-fidelity-digital-asset-derivatives-rfq-execution-system.jpg)

## Market Risk

Meaning ▴ Market Risk, in the context of crypto investing and institutional options trading, refers to the potential for losses in portfolio value arising from adverse movements in market prices or factors. </a><a href="https://prime.greeks.live/area/expected-shortfall/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A precision-engineered blue mechanism, symbolizing a high-fidelity execution engine, emerges from a rounded, light-colored liquidity pool component, encased within a sleek teal institutional-grade shell. This represents a Principal's operational framework for digital asset derivatives, demonstrating algorithmic trading logic and smart order routing for block trades via RFQ protocols, ensuring atomic settlement](https://options.greeks.live/wp-content/uploads/2025/07/institutional-crypto-derivatives-os-core-algorithmic-execution-engine.jpg)

## Expected Shortfall

Meaning ▴ Expected Shortfall (ES), also known as Conditional Value-at-Risk (CVaR), is a coherent risk measure employed in crypto investing and institutional options trading to quantify the average loss that would be incurred if a portfolio's returns fall below a specified worst-case percentile. </a><a href="https://prime.greeks.live/area/supervisory-approval/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A futuristic system component with a split design and intricate central element, embodying advanced RFQ protocols. This visualizes high-fidelity execution, precise price discovery, and granular market microstructure control for institutional digital asset derivatives, optimizing liquidity provision and minimizing slippage](https://options.greeks.live/wp-content/uploads/2025/07/advanced-rfq-protocols-for-digital-asset-derivatives-price-discovery.jpg)

## Supervisory Approval

Meaning ▴ Supervisory approval refers to the formal authorization or endorsement granted by a regulatory body, governmental agency, or an oversight committee for specific actions, products, or operational changes within a financial institution or crypto entity. </a><a href="https://prime.greeks.live/area/market-risk-models/?utm_source=options.greeks.live&utm_medium=referral&utm_campaign=satellite" class="glossary-item-box">
![A symmetrical, angular mechanism with illuminated internal components against a dark background, abstractly representing a high-fidelity execution engine for institutional digital asset derivatives. This visualizes the market microstructure and algorithmic trading precision essential for RFQ protocols, multi-leg spread strategies, and atomic settlement within a Principal OS framework, ensuring capital efficiency](https://options.greeks.live/wp-content/uploads/2025/07/precision-execution-engine-for-institutional-digital-asset-derivatives-rfq.jpg)

## Market Risk Models

Meaning ▴ Market Risk Models are quantitative frameworks engineered to measure and manage the potential financial losses an institution might experience due to adverse movements in market prices, encompassing factors such as interest rates, exchange rates, or commodity prices. </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">
![A luminous central hub with radiating arms signifies an institutional RFQ protocol engine. It embodies seamless liquidity aggregation and high-fidelity execution for multi-leg spread strategies](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-hub-for-optimal-liquidity-aggregation.jpg)

## Risk Factors

Meaning ▴ Risk Factors, within the domain of crypto investing and the architecture of digital asset systems, denote the inherent or external elements that introduce uncertainty and the potential for adverse outcomes. </a>

**Tags:** [Risk Factors](https://options.greeks.live/area/risk-factors/), [Risk Weight](https://options.greeks.live/area/risk-weight/), [Capital Efficiency](https://options.greeks.live/area/capital-efficiency/), [Supervisory Approval](https://options.greeks.live/area/supervisory-approval/), [Risk Management](https://options.greeks.live/area/risk-management/), [Standardised Approach](https://options.greeks.live/area/standardised-approach/)	

## Discover More

- 
### [How Does the Instrument by Instrument Approach Differ from Previous Models?](https://options.greeks.live/question/how-does-the-instrument-by-instrument-approach-differ-from-previous-models/)
![A precisely engineered multi-component structure, split to reveal its granular core, symbolizes the complex market microstructure of institutional digital asset derivatives. This visual metaphor represents the unbundling of multi-leg spreads, facilitating transparent price discovery and high-fidelity execution via RFQ protocols within a Principal's operational framework.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-grade-digital-asset-derivatives-rfq-protocols-revealing-market-microstructure-for-high-fidelity-execution-and-atomic-settlement-within-principals-operational-framework.jpg)

The instrument-by-instrument approach mandates a granular, bottom-up risk calculation, replacing portfolio-level models with a direct summation of individual position capital charges.

- 
### [How Do DLT-Based Atomic Swaps Change the Capital Requirements for Dark Pool Participants?](https://options.greeks.live/question/how-do-dlt-based-atomic-swaps-change-the-capital-requirements-for-dark-pool-participants/)
![A polished disc with a central green RFQ engine for institutional digital asset derivatives. Radiating lines symbolize high-fidelity execution paths, atomic settlement flows, and market microstructure dynamics, enabling price discovery and liquidity aggregation within a Prime RFQ.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-core-for-optimal-execution.jpg)

DLT-based atomic swaps reduce dark pool capital needs by collapsing settlement risk, turning static capital buffers into dynamic liquidity.

- 
### [How Does the Standardised Approach for CVA Differ from the Basic Approach?](https://options.greeks.live/question/how-does-the-standardised-approach-for-cva-differ-from-the-basic-approach/)
![A sleek, metallic mechanism with a luminous blue sphere at its core represents a Liquidity Pool within a Crypto Derivatives OS. Surrounding rings symbolize intricate Market Microstructure, facilitating RFQ Protocol and High-Fidelity Execution. This system enables Atomic Settlement, optimizing Capital Efficiency and Price Discovery for Institutional Grade Digital Asset Derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/prime-os-crypto-derivatives-rfq-protocol-core-mechanism.jpg)

The Standardised Approach for CVA is a sensitivity-based method rewarding hedging, unlike the simpler, formulaic Basic Approach.

- 
### [How Does the FRTB Framework Specifically Penalize Illiquid Assets?](https://options.greeks.live/question/how-does-the-frtb-framework-specifically-penalize-illiquid-assets/)
![An intricate, transparent cylindrical system depicts a sophisticated RFQ protocol for digital asset derivatives. Internal glowing elements signify high-fidelity execution and algorithmic trading. A central angular structure represents atomic settlement and multi-leg spread capabilities, ensuring best execution within institutional trading.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-execution-protocol-architecture.jpg)

FRTB systematically penalizes illiquid assets by increasing capital charges via non-modellable risk factors and longer liquidity horizons.

- 
### [What Are the Main Differences between Risk-Based Capital Requirements and the Leverage Ratio?](https://options.greeks.live/question/what-are-the-main-differences-between-risk-based-capital-requirements-and-the-leverage-ratio/)
![A polished, teal-hued digital asset derivative disc rests upon a robust, textured market infrastructure base, symbolizing high-fidelity execution and liquidity aggregation. Its reflective surface illustrates real-time price discovery and multi-leg options strategies, central to institutional RFQ protocols and principal trading frameworks.](https://options.greeks.live/wp-content/uploads/2025/07/digital-asset-derivatives-rfq-protocols-high-fidelity-institutional-execution.jpg)

Risk-based capital aligns capital with asset risk, while the leverage ratio provides a simple backstop based on total exposure.

- 
### [How Does the Frtb Framework Alter the Strategic Incentives for Model Selection?](https://options.greeks.live/question/how-does-the-frtb-framework-alter-the-strategic-incentives-for-model-selection/)
![Intersecting abstract geometric planes depict institutional grade RFQ protocols and market microstructure. Speckled surfaces reflect complex order book dynamics and implied volatility, while smooth planes represent high-fidelity execution channels and private quotation systems for digital asset derivatives within a Prime RFQ.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-rfq-protocols-digital-asset-microstructure-execution.jpg)

FRTB systemically links capital to data observability, forcing a granular, desk-level choice between IMA efficiency and SA stability.

- 
### [What Are the Primary Drivers for Banks Choosing the Standardised Approach over the Internal Model Approach?](https://options.greeks.live/question/what-are-the-primary-drivers-for-banks-choosing-the-standardised-approach-over-the-internal-model-approach/)
![Two abstract, segmented forms intersect, representing dynamic RFQ protocol interactions and price discovery mechanisms. The layered structures symbolize liquidity aggregation across multi-leg spreads within complex market microstructure. This visualizes institutional execution pathways, emphasizing atomic settlement and capital efficiency in digital asset derivatives.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-microstructure.jpg)

The shift to the Standardised Approach is driven by its operational simplicity and regulatory certainty in an era of rising model complexity and cost.

- 
### [What Are the Strategic Trade-Offs between the Standardised Approach and the Internal Model Approach under FRTB?](https://options.greeks.live/question/what-are-the-strategic-trade-offs-between-the-standardised-approach-and-the-internal-model-approach-under-frtb/)
![Clear geometric prisms and flat planes interlock, symbolizing complex market microstructure and multi-leg spread strategies in institutional digital asset derivatives. A solid teal circle represents a discrete liquidity pool for private quotation via RFQ protocols, ensuring high-fidelity execution.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocols-price-discovery-and-high-fidelity-execution.jpg)

The choice between FRTB's Standardised and Internal Model approaches is a strategic trade-off between operational simplicity and capital efficiency.

- 
### [What Are the Regulatory Capital Implications for a Bank Choosing Gross versus Net Margining?](https://options.greeks.live/question/what-are-the-regulatory-capital-implications-for-a-bank-choosing-gross-versus-net-margining/)
![A multi-faceted digital asset derivative, precisely calibrated on a sophisticated circular mechanism. This represents a Prime Brokerage's robust RFQ protocol for high-fidelity execution of multi-leg spreads, ensuring optimal price discovery and minimal slippage within complex market microstructure, critical for alpha generation.](https://options.greeks.live/wp-content/uploads/2025/07/institutional-digital-asset-derivatives-rfq-protocol-execution-precision-2.jpg)

The choice between gross and net margining dictates a bank's capital efficiency by directly impacting its calculated derivative exposures.

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    ]
}
```


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**Original URL:** https://options.greeks.live/question/how-do-internal-models-under-basel-ii-and-iii-affect-a-banks-capital-requirements/
