Executive Summary
Under the Fundamental Review of the Trading Book (FRTB), banks using the Internal Models Approach (IMA) must demonstrate that risk factors are supported by sufficient observable market data. This assessment is performed through the Risk Factor Eligibility Test (RFET). Risk factors that fail RFET become Non-Modellable Risk Factors (NMRFs), attracting additional capital charges that can materially increase market risk capital requirements.
Brickendon helps banks navigate this complex regulatory landscape by combining deep FRTB expertise, market risk knowledge, and data governance capabilities to build robust RFET frameworks, optimise NMRF management, and improve capital efficiency while maintaining regulatory compliance.
The Challenge Facing Banks
FRTB has fundamentally changed how banks demonstrate the validity of their internal market risk models. Regulators now require firms to prove that each risk factor used within IMA is supported by sufficient and reliable market evidence.
Failure to meet these requirements can result in large populations of NMRFs, increased capital charges, challenges to IMA approval, and greater operational complexity.
Brickendon supports institutions in addressing these challenges through end-to-end consulting services spanning risk methodology, regulatory interpretation, data management, operating model design, and technology implementation.
Understanding Risk Factors
A risk factor is any market variable that influences the value of a trading position (e.g., interest rates, credit spreads, equity prices, FX rates, commodity prices, volatility surface points, and correlations).
Example: a corporate bond’s value depends on the interest rate curve, the issuer’s credit spread, and relevant volatility measures, each treated as distinct risk factors under FRTB.
Brickendon helps firms establish consistent risk factor taxonomies, ownership frameworks, and governance structures that support accurate RFET assessments across trading businesses.
RFET: Purpose and Evidence
RFET determines whether a risk factor is sufficiently observable to be modelled within an approved internal model. A factor is modellable only if there is enough market evidence to measure its behaviour reliably.
Evidence is provided via Real Price Observations (RPOs). RPOs generally include: executed trades; exchange‑traded prices/transactions; and firm (committed) quotes that meet verification and governance standards. Approved vendor prices may count where they satisfy RPO criteria. Indicative quotes and unverified submissions typically do not qualify.
Brickendon assists banks in designing RFET frameworks that maximise the identification and capture of eligible RPOs while maintaining robust governance and auditability.
Why RFET Matters
Prior to FRTB, internal models were sometimes applied to illiquid risks with limited observable data. During stress, some assumptions proved unreliable and capital did not fully reflect uncertainty. RFET and the NMRF framework address this by tying modellability to demonstrable market activity.
For banks, the commercial implications are significant:
- Higher NMRF populations can increase market risk capital.
- RFET results directly influence IMA eligibility.
- Data quality and governance become strategic regulatory priorities.
- Technology and operating models must support ongoing compliance.
Brickendon helps clients transform RFET from a regulatory obligation into a strategic capital optimisation opportunity.
How RFET Determines Modellability
RFET is a data sufficiency assessment applied at the granularity of the defined risk factor (e.g., a specific curve tenor, or a strike–expiry node on a volatility surface). Neighbouring points are not automatically modellable unless permitted mapping/interpolation rules are satisfied.
The RFET process typically involves:
- Identifying and defining the risk factor.
- Collecting eligible RPOs from approved sources.
- Assessing observation frequency and time dispersion across the prescribed rolling period.
- Determining eligibility against regulatory thresholds.
- Applying permitted mapping and interpolation methodologies where appropriate.
Brickendon supports firms in designing, implementing, and validating these processes, ensuring consistency across trading desks, risk functions, and regulatory reporting frameworks.
Understanding NMRFs
A Non‑Modellable Risk Factor is any factor that fails RFET. Where market evidence is insufficient, the framework prescribes more conservative capitalisation through an NMRF charge.
Typical examples include illiquid corporate bond spreads, exotic option volatility points, structured credit, long‑dated emerging‑market instruments, sparse commodity locations/grades, and far‑tail cross‑currency basis tenors.
Brickendon helps banks identify the root causes of NMRF populations and develop targeted remediation strategies to improve modellability where feasible.
Capital Impact and Regulatory Consequences
Modellable risk factors can be captured within the Expected Shortfall (ES) framework, subject to regulatory approval.
NMRFs, however, are capitalised separately through a prescribed stress-based charge with constrained diversification benefits. Regulatory aggregation rules limit offsets between NMRFs and other risk factors, often resulting in materially higher capital requirements.
Brickendon’s specialists work with market risk, finance, and treasury functions to:
- Assess capital impacts
- Quantify optimisation opportunities
- Evaluate remediation scenarios
- Prioritise high-value RFET improvements
- Build sustainable governance frameworks
This allows firms to balance regulatory compliance with broader capital management objectives.
Common Drivers of NMRF Classification
Many NMRFs arise not only from illiquidity, but also from operational and data challenges, including:
- Insufficient market activity (e.g., structured/bespoke, thinly traded EM assets)
- Poor data capture (missing trades, unused firm quotes, incomplete histories)
- Fragmented sources (observations dispersed across systems/desks/vendors without aggregation)
- Weak governance (unclear ownership, insufficient audit trails/documentation, inadequate verification)
Brickendon brings extensive experience helping financial institutions address these issues through enhanced data governance, process redesign, and enterprise-wide risk data strategies.
How Brickendon Helps Reduce NMRFs
Leading organisations increasingly treat NMRF reduction as a strategic capital optimisation initiative.
Brickendon supports this through:
Data Optimisation
- Expansion of approved vendor coverage
- Enhanced RPO sourcing and capture
- Improved data quality controls
Governance Enhancement
- Clear ownership and accountability models
- Robust RFET policies and procedures
- Regulatory-ready audit trails and documentation
Technology and Architecture
- Centralised RFET repositories
- End-to-end data lineage
- Automated monitoring and reporting capabilities
Strategic Advisory
- Modellability trend analysis
- Desk-level performance monitoring
- Regulatory interpretation and implementation support
- Target operating model design
Why Partner with Brickendon?
RFET and NMRF management sit at the intersection of regulation, risk, data, technology, and capital management.
Brickendon’s consultants combine deep expertise across:
- FRTB implementation
- Market risk and capital modelling
- Data governance and data quality
- Regulatory change programmes
- Risk technology transformation
- Target operating model design
We help banks move beyond compliance, creating sustainable RFET capabilities that reduce operational burden, strengthen regulatory confidence, and deliver measurable capital benefits.
Every unnecessary NMRF comes at a cost.
Brickendon helps banks improve RFET performance, reduce unnecessary capital charges and build robust market risk frameworks that stand up to regulatory scrutiny.