Effective Risk Assessment and Strategic Planning

Stress Tests & Scenario Analysis

Comprehensive consulting for the development and implementation of stress tests and scenario analysis to assess your resilience and strategic preparation for multiple future developments.

  • Regulatory Compliance (EBA, BaFin)
  • Improved Risk Resilience
  • Optimized Capital Allocation

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

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Comprehensive Stress Tests and Scenario Analysis

Our Strengths

  • In-depth expertise in regulatory requirements (EBA, BaFin)
  • Experience with advanced modeling techniques
  • Proven implementation strategies

Expert Tip

The combination of quantitative stress test models and qualitative scenario techniques is crucial to ensure strategic agility in volatile markets and meet regulatory requirements.

ADVISORI in Numbers

11+

Years of Experience

120+

Employees

520+

Projects

We accompany you with a structured approach in the development and implementation of your stress tests and scenario analysis.

Our Approach:

Analysis of existing risk situation and processes

Development of customized stress test and scenario analysis frameworks

Implementation, training, and continuous improvement

"Effective stress tests and scenario analysis are crucial for risk resilience and strategic agility in an increasingly volatile and complex market environment."
Andreas Krekel

Andreas Krekel

Head of Risk Management, Regulatory Reporting

Expertise & Experience:

10+ years of experience, SQL, R-Studio, BAIS-MSG, ABACUS, SAPBA, HPQC, JIRA, MS Office, SAS, Business Process Manager, IBM Operational Decision Management

Our Services

We offer you tailored solutions for your digital transformation

Stress Test Design and Implementation

Development and implementation of customized stress test frameworks

  • Regulatory Stress Tests (EBA, BaFin)
  • Reverse Stress Tests
  • Multi-Factor Stress Tests

Scenario Analysis for Strategic Planning

Development and implementation of scenario analysis for strategic decisions

  • PESTEL Analysis and Trend Analysis
  • Strategic Implications Analysis
  • Integration into Decision Processes

Climate Risk Integration and ESG Stress Tests

Integration of climate risks and ESG factors into stress tests and scenario analysis

  • Physical and Transition Climate Risks
  • CO2 Price Path Scenarios
  • ESG Risk Assessment

Our Competencies in Financial Risk

Choose the area that fits your requirements

Credit Risk Management & Rating Procedures

Credit risk management and rating methods for financial institutions. Risk models, scoring systems and regulatory requirements.

Liquidity Management

Liquidity management and liquidity risk management for banks. LCR, NSFR, stress testing and regulatory liquidity requirements.

Market Risk Assessment & Limit Systems

Market risk assessment and limit systems for financial institutions. VaR, expected shortfall, sensitivities and regulatory capital requirements.

Model Development

Risk model development for financial institutions. Credit, market and operational risk models to regulatory standards.

Model Governance

Model governance framework for financial institutions. Model risk management, validation, inventory and regulatory requirements.

Model Validation

Model validation for risk models per MaRisk, EBA and BCBS. Independent review of model quality, assumptions and regulatory conformity.

Portfolio Risk Analysis

Portfolio risk analysis and management for financial institutions. Diversification, concentration, stress testing and capital allocation.

Frequently Asked Questions about Stress Tests & Scenario Analysis

What are stress tests and how do they differ from scenario analysis?

Stress tests and scenario analysis are complementary risk management instruments with different focuses:

🔍 Stress Tests

Definition: Analysis of the impact of extreme but plausible events on a company's financial or operational stability
Focus: Quantitative assessment of resilience to specific shocks
Time Horizon: Typically short-term (immediate impacts)
Application Area: Primarily risk management and regulatory compliance
Example: Impact of a 35% stock market crash on capital adequacy

📊 Scenario Analysis

Definition: Examination of coherent future scenarios incorporating multiple risk factors and trends
Focus: Qualitative and quantitative assessment of various possible future developments
Time Horizon: Medium to long-term (strategic perspective)
Application Area: Strategic planning and decision-making
Example: Development of electromobility strategy under various technological and regulatory scenarios

🔄 Complementary Aspects

Methodological Integration: Stress tests can be part of more comprehensive scenario analysis
Data Foundation: Both use historical data, expert assessments, and model projections
Decision Support: Both provide insights for management and supervisory bodies
Regulatory Context: Increasing convergence through supervisory requirements (e.g., EBA guidelines)

What types of stress tests exist?

Various types of stress tests exist, deployed depending on application area and objectives:

🔍 By Risk Factor Coverage

Sensitivity Analysis: Isolated shocks to individual risk factors (e.g., interest rate increase of

200 basis points)

Multi-Factor Stress Tests: Simultaneous shocks to multiple risk factors considering correlations
Systemic Stress Tests: Consideration of contagion effects and feedback loops in the financial system

📊 By Scenario Design

Historical Scenarios: Replication of past crisis periods (e.g.,

2008 financial crisis,

2020 COVID‑19 shock)

Hypothetical Scenarios: Simulation of plausible but not yet occurred events
Hybrid Scenarios: Combination of historical experiences with hypothetical elements

️ By Methodological Approach

Reverse Stress Tests: Identification of scenarios that would lead to predefined critical losses or company collapse
Bottom-up Stress Tests: Detailed modeling at individual position level
Top-down Stress Tests: Aggregated modeling at portfolio level

🌱 By Risk Types

Market Risk Stress Tests: Focus on market price changes (equities, interest rates, currencies, commodities)
Credit Risk Stress Tests: Analysis of default probabilities and loss rates
Liquidity Stress Tests: Assessment of payment capacity under stress conditions
Operational Stress Tests: Simulation of system failures, cyber attacks, or process errors
Climate Stress Tests: Analysis of physical and transitional climate risks

🏢 By Regulatory Context

Supervisory Stress Tests: Scenarios and methodology prescribed by regulatory authorities (e.g., EBA stress tests for banks)
Internal Stress Tests: Tests developed and conducted by the company itself
ICAAP/ILAAP Stress Tests: Within the framework of internal capital and liquidity adequacy processes

How do you develop an effective stress test framework?

Developing an effective stress test framework comprises several key components:

🎯 Strategic Foundations

Define Objectives: Clear definition of goals (regulatory compliance, capital planning, risk management)
Establish Governance Structure: Roles, responsibilities, and decision processes
Integrate Risk Appetite: Link with overarching risk framework
Observe Proportionality Principle: Appropriateness to company size and complexity

📊 Scenario Design

Identify Risk Factors: Systematic capture of relevant risk drivers
Calibrate Scenarios: Determine shock intensity (historical data, expert assessments)
Consider Correlations: Realistic representation of dependencies between risk factors
Define Time Horizons: Short-term shocks vs. longer-term developments
Ensure Scenario Consistency: Logical coherence of assumptions

️ Modeling Approach

Determine Granularity: Level of detail in modeling (individual position vs. portfolio)
Select Methods: Statistical models, simulation techniques, expert estimates
Define Data Foundation: Requirements for quality, timeliness, and completeness
Establish Validation Process: Verification of model accuracy and solidness
Document Limitations: Transparency about model assumptions and boundaries

📈 Implementation and Operationalization

Build IT Infrastructure: Systems for data management and calculation
Process Integration: Integration into existing risk management and planning processes
Determine Automation Level: Balance between efficiency and control
Create Documentation: Comprehensive description of methods, assumptions, and processes
Develop Training Program: Competence building among relevant employees

🔄 Reporting and Action Derivation

Define Report Formats: Target group-appropriate presentation of results
Set Thresholds: Triggers for actions when exceeded
Establish Escalation Processes: Clear paths for critical results
Develop Action Catalog: Predefined action options for various scenarios
Establish Feedback Loop: Continuous improvement of the framework

What regulatory requirements exist for stress tests?

Regulatory requirements for stress tests vary by industry and region but typically include:

🏦 Banks and Financial Institutions

EBA Guidelines 2018‑04: Comprehensive requirements for stress test management - Differentiation between sensitivity analysis and scenario stress tests - Requirements for anchor scenarios as reference points - Integration into ICAAP/ILAAP processes
Basel Framework: Specific requirements for various risk types - Market Risk: Expected Shortfall under stress periods - Credit Risk: Downturn-LGD and Stress-PD - Liquidity Risk: LCR and NSFR under stress conditions
MaRisk (Germany): Detailed specifications for design - AT 4.3.2: Integration into risk-bearing capacity concept - BTR 1‑4: Specific requirements per risk type

🏢 Insurance Companies

Solvency II: Stress tests as part of ORSA process - Own Risk and Solvency Assessment - Reverse stress tests to identify existential threats
BaFin Requirements: Standardized stress parameters - R 10: 10% decline in bond prices - A 35: 35% stock market crash - RA 25: Combined shock of -5% bonds and -20% equities

🏭 Non-Financial Companies

Corporate Governance Code: Risk management requirements - Appropriate early risk detection systems - Regular reporting to supervisory bodies
IDW PS 340: Audit standard for early risk detection system - Identification of going-concern risks - Documentation of stress test results

🌱 Climate-Related Requirements (cross-industry)

TCFD Recommendations (Task Force on Climate-related Financial Disclosures) - Scenario analysis for physical and transitional climate risks - Disclosure of methodology and results
ECB Guide on Climate Risks - Integration of climate scenarios into existing stress test frameworks - Consideration of various temperature paths (1.5°C, 2°C, 3°C+)

📋 Overarching Requirements

Governance and Responsibilities - Involvement of board and supervisory board - Clear assignment of roles and competencies
Documentation and Traceability - Comprehensive description of methods and assumptions - Audit trail for model changes
Validation and Quality Assurance - Regular review of model quality - Independent control by risk control function

How do you conduct scenario analysis for strategic decisions?

Scenario analysis for strategic decisions follows a structured process:

🎯 Preparation and Focusing

Define Strategic Question: Precise formulation of the decision to be examined
Set Time Horizon: Typically 3–10 years for strategic analysis
Involve Stakeholders: Early integration of relevant decision-makers and experts
Resource Planning: Determination of budget, timeframe, and required expertise

🔍 Environmental Analysis and Influence Factor Identification

PESTEL Analysis: Systematic capture of political, economic, social, technological, ecological, and legal factors
Trend Analysis: Identification of long-term developments with high probability of occurrence
Uncertainty Analysis: Determination of factors with high uncertainty and high influence
Expert Interviews: Obtaining various perspectives on key factors
Cross-Impact Analysis: Assessment of interactions between influence factors

📊 Scenario Development

Define Scenario Logic: Determination of main axes of uncertainty
Span Scenario Framework: Typically 3–5 distinct, plausible future scenarios
Develop Narratives: Formulation of coherent stories for each scenario
Consistency Check: Ensuring internal logic of each scenario
Quantification: Translation of qualitative descriptions into measurable parameters

️ Strategic Implications Analysis

Solidness Analysis: Assessment of existing strategies under all scenarios
Opportunity-Risk Assessment: Identification of specific opportunities and threats per scenario
Option Development: Derivation of strategic action alternatives
Flexibility Analysis: Assessment of adaptability of various options
No-Regret Moves: Identification of measures beneficial in all scenarios

🔄 Integration into Decision Processes

Strategy Adjustment: Modification of existing or development of new strategies
Early Warning Indicators: Definition of signals for development toward specific scenarios
Continuous Monitoring: Regular review of scenario relevance
Communication Plan: Conveyance of scenarios and derived strategies
Implementation Planning: Concrete steps for implementing chosen strategy

How do you integrate climate risks into stress tests and scenario analysis?

Integrating climate risks into stress tests and scenario analysis requires a specialized approach:

🌡 ️ Climate Scenario Frameworks

NGFS Scenarios (Network for Greening the Financial System) - Orderly Transition: Early and gradual climate policy - Disorderly Transition: Delayed and abrupt measures - Hot House World: Insufficient measures with severe physical consequences
IEA Scenarios (International Energy Agency) - Net Zero Emissions by

2050 (NZE)

Announced Pledges Scenario (APS)
Stated Policies Scenario (STEPS)
IPCC Pathways (Intergovernmental Panel on Climate Change) - SSP1‑1.9: Sustainable development (1.5°C target) - SSP2‑4.5: Middle way (2.7°C warming) - SSP5‑8.5: Fossil-intensive scenario (4.4°C warming)

🔍 Risk Typology

Physical Risks - Acute Risks: Extreme weather events (floods, storms, heat waves) - Chronic Risks: Long-term climate changes (sea level rise, desertification)
Transition Risks - Political Risks: CO 2 pricing, regulations, bans - Technological Risks: Effective innovations, stranded assets - Market Risks: Changed consumer behavior, commodity price volatility - Reputational Risks: Changed stakeholder expectations

📊 Modeling Approaches

Top-down Approach - Macroeconomic Models: Representation of economy-wide effects - Sectoral Vulnerability Matrices: Industry-specific impacts - CO 2 Price Paths: Dynamic simulation of pricing scenarios (€50–€200/t)
Bottom-up Approach - Geolocalized Exposures: Location-specific physical risks - Technology Pathways: Detailed analysis of technology disruptions - Emission Intensity: Granular analysis at company level

️ Practical Implementation

Time Horizons - Short-term (1–5 years): Focus on transition risks and acute physical risks - Medium-term (5–10 years): Combination of transition and physical risks - Long-term (10–30 years): Comprehensive integration of all climate risks
Data Sources - Climate Models: CMIP6, regionalized climate projections - Emission Data: Scope 1–3 emissions from companies - Geographic Information Systems: Location data and natural hazard maps
Governance - Climate Risk Committee: Specialized body for climate stress tests - Expert Involvement: Climate scientists, economists, industry experts - Reporting: Integration into regular risk reporting

🔄 Case Example: Climate Stress Test for Financial Institutions

Model Parameters - Horizon: 2030/2050 - CO 2 Price: €75–€150/t - Physical Risks: Increased frequency of natural disasters
Insights - Steel Industry: Default probability +18% - Energy Sector: Equity requirement +34%

What are reverse stress tests and how are they conducted?

Reverse stress tests are an advanced risk management instrument with specific methodology:

🎯 Concept and Objectives

Definition: Identification of scenarios that would lead to company collapse or predefined critical losses
Regulatory Context: Mandatory component of ORSA process for insurers and ICAAP for banks
Perspective Shift: Reversal of classic stress test logic (from result to scenario)
Added Value: Uncovering blind spots in risk management and identifying existential threats

📊 Methodological Approaches

Reverse Engineering - Definition of critical state (e.g., falling below regulatory capital ratios) - Backward calculation to determine necessary shock intensities - Iterative adjustment of risk factors until reaching critical state
Bayesian Networks - Modeling of dependency structures between risk factors - Conditional probabilities for various risk combinations - Identification of plausible paths to critical state
Optimization Algorithms - Objective Function: Minimization of shock intensity while reaching critical state - Constraints: Plausibility limits for risk factors - Solution Methods: Genetic algorithms, simulated annealing

️ Practical Implementation

Preparation Phase - Definition of critical thresholds (e.g., solvency ratio <100%, liquidity ratio <85%) - Identification of relevant risk factors and their mechanisms - Determination of plausibility limits for risk factor characteristics
Modeling Phase - Development of mathematical relationships between risk factors and critical metrics - Calibration of sensitivities and correlations - Implementation of chosen methodological approach
Analysis Phase - Calculation of various scenarios leading to critical state - Assessment of plausibility and probability of occurrence - Identification of risk clusters and vulnerabilities
Action Derivation - Development of preventive measures for identified weaknesses - Definition of early warning indicators for critical developments - Integration into emergency management and capital planning

🔄 Application Examples

Banks - Identification of market constellations leading to falling below minimum capital ratio - Analysis of liquidity shortages that could lead to payment default
Insurance Companies - Determination of catastrophe scenarios threatening solvency ratio - Analysis of capital market developments impairing asset-liability coverage
Industrial Companies - Identification of supply chain disruptions leading to production shutdown - Analysis of market developments pushing profitability below critical thresholds

What role do stress tests and scenario analysis play in strategic planning?

Stress tests and scenario analysis fulfill several important functions in strategic planning:

🎯 Strategic Decision Support

Solidness Testing: Assessment of resilience of strategic options under various future conditions
Option Evaluation: Comparative analysis of alternative strategies under multiple scenarios
Risk-Return Optimization: Identification of strategies with optimal balance between opportunities and risks
Prioritization: Focus on critical uncertainties with high strategic impact

🔍 Expansion of Strategic Perspective

Overcoming Cognitive Biases: Reduction of groupthink and confirmation bias
Identification of Blind Spots: Uncovering overlooked risks and opportunities
Perspective Expansion: Integration of different stakeholder viewpoints
Early Warning System: Recognition of weak signals for effective changes

📊 Integration into Strategic Planning Process

Strategy Development: Input for formulation of vision, mission, and strategic goals
Strategic Analysis: Complement to classic methods like SWOT or Porter's Five Forces
Strategy Implementation: Development of adaptive implementation paths
Strategic Controlling: Continuous review of scenario relevance

️ Practical Application Examples

Product Strategy - Electromobility strategy of automotive manufacturer under various technology and regulatory scenarios - Development of flexible production designs to reduce CAPEX misallocation by 15%
Market Entry Strategy - Assessment of various market entry options considering geopolitical uncertainties - Development of trigger points for go/no-go decisions
Investment Strategy - Portfolio optimization under various macroeconomic scenarios - Identification of no-regret investments with positive performance in all scenarios
Sustainability Strategy - Development of decarbonization pathways under various CO 2 price scenarios - Assessment of physical climate risks for global production sites

🔄 Success Factors for Strategic Integration

Executive Sponsorship: Support from top management
Process Integration: Anchoring in regular strategy processes
Communication: Understandable presentation of complex scenarios
Continuity: Regular updating and further development
Action Orientation: Focus on concrete strategic implications

What trends are shaping the future of stress tests and scenario analysis?

The future of stress tests and scenario analysis is shaped by several effective trends:

🤖 Technological Innovation

AI and Machine Learning - Automated scenario generation through generative AI - Detection of complex risk relationships through deep learning - Natural Language Processing for analysis of qualitative scenario descriptions
Big Data and Advanced Analytics - Integration of alternative data sources (satellite data, social media, IoT) - Real-time stress tests with continuous data updating - Granular modeling at individual position level
Quantum Computing - Complex Monte Carlo simulations with exponentially higher speed - Optimization of reverse stress tests through quantum annealing - Modeling of high-dimensional correlation structures

🌱 Content Expansion

Climate Risk Integration - Physical Climate Risks: Detailed geolocalized modeling - Transition Risks: Sector-specific CO 2 price paths - Biodiversity Risks: Assessment of natural capital and ecosystem services
Cyber Resilience - Simulation of complex cyber attacks and system failures - Assessment of contagion effects in networked systems - Integration of cyber-physical systems in stress tests
Geopolitical Complexity - Fragmentation of global markets and supply chains - Technological decoupling and digital sovereignty - Resource conflicts and trade barriers

📊 Methodological Development

Adaptive Scenario Analysis - Dynamic adjustment of scenarios to new information - Bayesian updating of probabilities - Agile scenario processes with shorter cycles
Multi-Period Stress Tests - Modeling of feedback effects and management reactions - Path-dependent analysis instead of static shocks - Integration of system dynamics models
Integrated Risk Modeling - Overcoming silo structures between risk types - Consistent aggregation of various risks - Consideration of risk-risk interactions

️ Organizational Transformation

Democratization of Stress Tests - Self-service tools for business units - Visualization platforms for interactive scenario analysis - Collaborative scenario processes with broad stakeholder participation
Integration into Decision Processes - Embedding in operational decisions (not just strategic planning) - Linking with performance management and incentive systems - Continuous risk monitoring instead of periodic stress tests
Competence Development - Data science and AI expertise in risk management - Interdisciplinary teams of risk managers, data analysts, and subject matter experts - Promotion of scenario thinking in corporate culture

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Success Stories

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Digitalization in Steel Trading

Klöckner & Co

Digital Transformation in Steel Trading

Case Study
Digitalisierung im Stahlhandel - Klöckner & Co

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

Siemens

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

Case Study
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

Bosch

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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