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FRTB Internal Models Approach (IMA) — Requirements, Approval and Implementation

The FRTB Internal Models Approach (IMA) allows banks to use their own risk models for market risk capital calculations — provided they meet strict supervisory requirements for Expected Shortfall, backtesting and P&L attribution. As specialist FRTB consultants, ADVISORI supports institutions with IMA approval, model validation and ongoing compliance.

  • ✓IMA approval support: gap analysis, desk-level approval and supervisory dialogue
  • ✓Expected Shortfall modelling to FRTB specifications (97.5% quantile, variable liquidity horizons)
  • ✓P&L Attribution Test (PLAT) and backtesting: setup, calibration and documentation
  • ✓NMRF management: identification of non-modellable risk factors and stressed ES calculation

Your strategic success starts here

Our clients trust our expertise in digital transformation, compliance, and risk management

30 Minutes • Non-binding • Immediately available

For optimal preparation of your strategy session:

  • Your strategic goals and objectives
  • Desired business outcomes and ROI
  • Steps already taken

Or contact us directly:

info@advisori.de+49 69 913 113-01

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IMA timeline: CRR III postpones IMA requirement to January 2028

While the FRTB trading book boundary and Standardised Approach take effect from January 2027, the IMA application requirement has been postponed to January 2028. Institutions should use the remaining time for model development, data infrastructure build-out and test runs.

ADVISORI in Numbers

11+

Years of Experience

120+

Employees

520+

Projects

We guide you from strategic approach selection through technical model development to successful supervisory approval of the IMA.

Our Approach:

Cost-benefit analysis: IMA vs. SA — assessing capital savings potential per desk

Build Expected Shortfall model: risk factor mapping, liquidity horizons (10-120 days), stressed ES

Implement P&L Attribution Test and backtesting: thresholds, traffic light system, fallback rules

Establish NMRF process: Real Price Observation test, stressed capital add-on for non-modellable factors

Create desk-level approval packages: documentation, model description, validation report

Prepare supervisory dialogue and actively support the examination process

"Intelligent optimization of the FRTB Internal Models Approach is the key to sustainable Basel III Internal Models compliance and regulatory excellence in modern banking. Our model validation solutions enable institutions not only to meet supervisory requirements but also to develop strategic compliance advantages through optimized model development and predictive market risk assessment. By combining in-depth Internal Models expertise with modern technologies, we create lasting competitive advantages while protecting sensitive company data."
Melanie Düring

Melanie Düring

Head of Risk Management

Our Services

We offer you tailored solutions for your digital transformation

IMA Approval and Desk-Level Authorisation

We support the entire approval process — from desk structure analysis through application preparation to supervisory dialogue with regulators.

  • Gap analysis of existing market risk infrastructure against IMA requirements
  • Desk-level eligibility assessment: which desks benefit from the IMA?
  • Preparation of supervisory documentation and model applications
  • Support during the regulatory examination process and remediation

Expected Shortfall and Model Validation

Building and validating the ES calculation methodology to FRTB specifications — including variable liquidity horizons and multiplier calibration.

  • Expected Shortfall calculation: 97.5% quantile with risk-class-specific horizons
  • Stress testing and scenario analysis for market risk capital
  • Model validation per EBA RTS: independent review and documentation
  • Calibration of the supervisory multiplier (factor 1.5)

PLAT, Backtesting and NMRF Management

Implementation of the quantitative tests that determine desk-level approval — P&L Attribution, backtesting and Non-Modellable Risk Factors.

  • P&L Attribution Test (PLAT): building comparison logic between hypothetical and actual P&L
  • Backtesting framework: traffic light approach, escalation rules
  • NMRF identification: Real Price Observation test and data requirements
  • Calculate and document stressed ES add-on for non-modellable risk factors

Our Competencies in Fundamental Review of the Trading Book (FRTB)

Choose the area that fits your requirements

Expected Shortfall Under FRTB – Calculation, Validation and Implementation

Expected Shortfall (ES) is the central risk measure for market risk capital requirements under the Fundamental Review of the Trading Book (FRTB). It replaces Value at Risk and measures the average loss in the tail of the loss distribution — at the 97.5% confidence level over a 250-day stress period. ADVISORI guides banks through implementation: from ES calculation through classification of modellable risk factors to regulatory validation.

FRTB Backtesting Requirements — Model Validation Standards for Market Risk

FRTB Backtesting Requirements demand precise implementation of Basel III model validation with specific backtesting performance requirements and validation procedures. As a leading consulting firm, we develop tailored RegTech solutions for intelligent backtesting compliance, automated model performance monitoring, and strategic validation optimization with full IP protection.

FRTB Boundary Trading Banking Book

The correct delineation between the trading book and banking book is critical for FRTB compliance and capital optimization. Together with you, we develop solid boundary management frameworks for precise classification and efficient management.

FRTB Credit Valuation Adjustment

FRTB Credit Valuation Adjustment presents new challenges for capital calculation and risk management. Together with you, we develop comprehensive CVA frameworks for precise capital calculation, effective hedging, and sustainable compliance excellence.

FRTB Data Management

The Fundamental Review of the Trading Book demands comprehensive market data, demonstrable risk factor modellability and audit-proof data governance. We build the data infrastructure your trading book needs — from real price observation pipelines and NMRF minimisation to automated data quality assurance.

FRTB German Implementation

The Fundamental Review of the Trading Book presents German banks with specific challenges. We develop tailored implementation strategies that meet BaFin requirements while accounting for the particularities of the German banking market.

FRTB Implementation

Navigate the complex implementation of the Fundamental Review of the Trading Book with our comprehensive implementation support. We guide you through the entire process – from the initial assessment and gap analysis through concept development and system adaptation to full integration into your trading and risk management systems, including model adjustment, data infrastructure and process optimisation.

FRTB Implementation Strategy: Approach Selection, Capital Optimization & Phased Rollout

FRTB Implementation Strategy requires precise implementation of the Basel III Fundamental Review of the Trading Book with specific market risk capital requirements and supervisory validation. As a leading AI consultancy, we develop tailored RegTech solutions for intelligent FRTB compliance, automated trading book separation and strategic market risk optimization with full IP protection.

FRTB Market Risk Modeling – Sensitivity-Based Approach, Risk Classes & Risk Factor Modeling

The Fundamental Review of the Trading Book requires fundamentally new market risk modeling: The sensitivity-based approach (SbA) calculates delta, vega and curvature risks across seven risk classes – GIRR, CSR (non-sec, sec CTP, sec non-CTP), equity, FX and commodity. We support banks in the methodological design, risk factor modeling and operational implementation of these requirements.

FRTB Non-Modellable Risk Factors (NMRF) – RPO Test & SES Capital Add-On | ADVISORI

FRTB Non-Modellable Risk Factors require precise implementation of Basel III NMRF identification with specific capital calculation procedures and stress scenario calibration. As a leading AI consultancy, we develop tailored RegTech solutions for intelligent NMRF compliance, automated risk factor validation and strategic supervisory recognition optimization with full IP protection.

FRTB Ongoing Compliance

Ongoing adherence to FRTB requirements demands systematic monitoring, regular adjustments, and proactive optimization. We support you in establishing sustainable FRTB compliance.

FRTB P&L Attribution Test (PLAT) – Requirements, Methodology & Consulting | ADVISORI

FRTB Profit & Loss Attribution requires precise implementation of Basel III P&L allocation with specific risk factor decomposition requirements and model validation. As a leading AI consultancy, we develop tailored RegTech solutions for intelligent P&L attribution compliance, automated backtesting integration and strategic transparency optimisation with full IP protection.

FRTB Readiness Assessment

Our comprehensive FRTB readiness assessment identifies gaps in your current systems, processes, and data, quantifies the impact on your capital, and delivers a tailored implementation roadmap for efficient FRTB compliance.

Frequently Asked Questions about FRTB Internal Models Approach (IMA) — Requirements, Approval and Implementation

What is the FRTB Internal Models Approach and how does it differ from the Standardised Approach?

The Internal Models Approach (IMA) allows banks to use their own risk models to calculate market risk capital requirements. Unlike the Standardised Approach (SA-FRTB), which prescribes fixed risk weights, the IMA is based on Expected Shortfall (ES) at the 97.5% quantile. The goal: more risk-sensitive and potentially lower capital requirements — provided the bank meets strict requirements for model quality, backtesting and P&L attribution. The capital formula reads IMA capital = IMCC + NMRF + DRC.

What requirements does IMA approval place on individual trading desks?

IMA approval operates at desk level — each trading desk must be individually authorised. Prerequisites are passing backtesting examinations (traffic light approach) and the P&L Attribution Test (PLAT). Desks that fail these tests automatically fall back to the Standardised Approach. Additionally, each desk must demonstrate qualified risk management infrastructure, sufficient data history and independent model validation.

What is the P&L Attribution Test (PLAT) and why is it critical?

The P&L Attribution Test compares actual trading P&L results with the values predicted by the risk model. The deviation is assessed using statistical thresholds (Spearman correlation and Kolmogorov-Smirnov test). If a desk fails the PLAT, it loses IMA eligibility and must use the more capital-intensive Standardised Approach. The PLAT is therefore the central quality test for model accuracy under FRTB.

How does the Expected Shortfall model work under the IMA?

The Expected Shortfall model calculates the expected loss beyond the 97.5% quantile — capturing tail risks better than the previous Value-at-Risk. Under the FRTB, risk-class-specific liquidity horizons of

10 to

120 days apply. The IMCC (Internal Model Capital Charge) is calculated from the weighted combination of current and stressed ES values, multiplied by the supervisory factor of 1.5.

What are Non-Modellable Risk Factors (NMRF) and how are they treated?

Risk factors that fail the Real Price Observation (RPO) test — those not sufficiently supported by observable market prices — are classified as non-modellable (NMRF). A separate stressed Expected Shortfall add-on must be calculated for these factors, which is added to the IMA capital. The NMRF treatment is often the most capital-intensive part of the IMA and requires a systematic data strategy.

What role does backtesting play in IMA approval?

Backtesting compares model predictions with actual losses over a period of

250 trading days. Results are assessed using the traffic light approach: green zone (0–4 exceedances), amber zone (5‑9) and red zone (10+). In the red zone, the supervisor may withdraw IMA approval. Backtesting must be performed and documented at both desk and firm-wide level.

When does the IMA requirement take effect under CRR III?

The EU has postponed the IMA application requirement to January 2028, while the FRTB trading book boundary and Standardised Approach already take effect from January 2027. Banks wishing to use the IMA should use the remaining time for model development, data infrastructure, test runs and the supervisory approval process. The EBA has already published final RTS on liquidity horizons, backtesting and risk factor modellability.

How does ADVISORI support banks with IMA implementation?

ADVISORI guides institutions from strategic assessment (IMA vs. SA: is the IMA worthwhile for which desks?) through technical model development (ES calculation, PLAT, backtesting, NMRF) to supervisory documentation and regulatory dialogue. Our consultants bring experience from IMA approval projects at European banks and support both initial approval and ongoing model monitoring and recalibration.

What does the transition to the FRTB Internal Models Approach cost?

IMA implementation requires significant investment in model infrastructure, data management and personnel. Typical cost drivers include risk factor modelling, PLAT infrastructure build-out, NMRF data requirements and supervisory documentation. These are offset by potentially much lower capital requirements — for large trading books, the IMA capital saving compared to the SA can amount to several hundred million euros.

Which EBA standards govern the IMA under CRR III?

The EBA has published several final Regulatory Technical Standards (RTS) on the IMA: RTS on liquidity horizons for risk factor mapping, RTS on backtesting and P&L attribution requirements, and RTS on risk factor modellability (NMRF criteria). These standards define the technical details of IMA implementation and have been published in the EU Official Journal since November 2022.

Success Stories

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Results

Over 2 billion euros in annual revenue through digital channels
Goal to achieve 60% of revenue online by 2022
Improved customer satisfaction through automated processes

AI-Powered Manufacturing Optimization

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Smart Manufacturing Solutions for Maximum Value Creation

Case Study
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Results

Significant increase in production performance
Reduction of downtime and production costs
Improved sustainability through more efficient resource utilization

AI Automation in Production

Festo

Intelligent Networking for Future-Proof Production Systems

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FESTO AI Case Study

Results

Improved production speed and flexibility
Reduced manufacturing costs through more efficient resource utilization
Increased customer satisfaction through personalized products

Generative AI in Manufacturing

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AI Process Optimization for Improved Production Efficiency

Case Study
BOSCH KI-Prozessoptimierung für bessere Produktionseffizienz

Results

Reduction of AI application implementation time to just a few weeks
Improvement in product quality through early defect detection
Increased manufacturing efficiency through reduced downtime

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