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Optimal risk data aggregation and reporting for financial institutions

BCBS-239

The BCBS-239 guidelines place high demands on the risk data aggregation and reporting of financial institutions. We support you in achieving full compliance and optimizing your data architecture.

  • ✓Improved data quality and governance for precise risk reports
  • ✓Optimized data architecture for efficient risk data aggregation
  • ✓Efficient reporting for well-founded decision-making in risk management
  • ✓Comprehensive compliance with regulatory requirements

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

Certifications, Partners and more...

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BCBS-239 Compliance

Our Strengths

  • Comprehensive expertise in banking regulation and specifically BCBS-239
  • Many years of experience in implementing data governance structures
  • Proven methodology for optimizing risk data processes
  • Comprehensive approach that integrates technology, processes, and organization
⚠

Expert Tip

BCBS-239 compliance is more than just a regulatory obligation – it forms the foundation for modern, data-driven risk management and can lead to significant efficiency gains and better strategic decisions.

ADVISORI in Numbers

11+

Years of Experience

120+

Employees

520+

Projects

Together with you, we develop a tailored strategy for BCBS-239 compliance that is aligned with your specific requirements and existing data architecture.

Our Approach:

Analysis of existing risk data processes and identification of compliance gaps

Development of a comprehensive BCBS-239 compliance roadmap

Implementation of data governance structures and processes

Optimization of data architecture for efficient risk data aggregation

Development and implementation of reporting solutions

"BCBS-239 is more than just a regulatory obligation – it is a central lever for data quality and governance capability. With our structured approach and deep subject matter expertise, we support organizations not only in meeting requirements on time, but in substantially improving their risk data aggregation and reporting processes. Those who act now lay the foundation for sound decisions and regulatory security."
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

LinkedIn Profile

Our Services

We offer you tailored solutions for your digital transformation

BCBS-239 Gap Analysis and Compliance Assessment

We analyze your existing risk data processes and systematically identify compliance gaps with respect to BCBS-239.

  • Comprehensive analysis of the risk data infrastructure
  • Assessment of data quality and governance
  • Identification of compliance gaps
  • Prioritization of action requirements

Data Governance and Architecture Optimization

We support you in implementing robust data governance structures and optimizing your data architecture for efficient BCBS-239 compliance.

  • Development of a data governance framework
  • Definition of data ownership and responsibilities
  • Optimization of data architecture for efficient risk data aggregation
  • Implementation of data quality controls

Looking for a complete overview of all our services?

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Our Areas of Expertise in Regulatory Compliance Management

Our expertise in managing regulatory compliance and transformation, including DORA.

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BCBS 239

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Frequently Asked Questions about BCBS-239

What strategic business benefits does full BCBS-239 compliance offer beyond regulatory requirements?

BCBS‑239 compliance transcends the mere fulfillment of regulatory requirements and opens up far-reaching strategic opportunities for forward-looking financial institutions. A robust risk data infrastructure forms the foundation for data-driven decision-making and strategic competitive advantages in an increasingly digitalized financial world.

🎯 Strategic business benefits beyond compliance:

• Accelerated decision-making processes: High-quality, timely risk data enables significantly faster and better-informed decision-making at all management levels – from tactical risk management to strategic investment decisions.
• Competitive advantages through data excellence: Institutions with superior data infrastructure can identify market opportunities more quickly, assess them more precisely, and act on them more decisively than competitors with fragmented data systems.
• Cost optimization through process efficiency: The consolidation and standardization of risk data processes leads to measurable efficiency gains, reduced operating costs, and a reduction in manual interventions of up to 70%.
• Strategic agility: The ability to identify and quantify risks precisely enables proactive adaptation to changing market conditions and regulatory requirements.

💡 Transformative potential through BCBS‑239 compliance:

• Foundation for advanced analytics and AI: A consolidated, high-quality risk data architecture is the indispensable basis for the successful use of machine learning and AI in risk management.
• Enabler for new business models: Improved risk data transparency enables the development of innovative financial products and services with more differentiated risk models.
• Improved capital management: More precise risk assessments lead to more efficient capital allocation, optimized cost of capital, and potentially higher returns on equity.
• Increased stakeholder confidence: A demonstrably sound risk data infrastructure strengthens the confidence of investors, rating agencies, and other stakeholders in the institution's governance.

How can we concretely monetize the substantial investments in BCBS-239 compliance and ensure a measurable ROI?

Monetizing BCBS‑239 investments requires a multidimensional approach that quantifies both direct cost savings and strategic value creation. ADVISORI supports financial institutions in achieving a demonstrable ROI and turning the compliance transformation into a sustainable competitive advantage.

💰 Direct financial benefits and cost savings:

• Reduction of regulatory buffers: More precise risk quantification can reduce regulatory capital add-ons (Pillar 2) by up to 15–25%, with direct implications for capital efficiency and RoE.
• Automation gains: The standardization and automation of manual processes in risk data aggregation can reduce operating costs by 20–30% while significantly reducing error rates.
• Shorter reporting cycles: Optimizing the data architecture can reduce the time required for regulatory reporting by 40–60%, freeing up resources for value-adding activities.
• Avoidance of regulatory sanctions: Robust BCBS‑239 compliance minimizes the risk of fines, which can quickly run into double-digit millions for large financial institutions.

📈 Strategic value creation levers and ROI potential:

• Data-driven innovation: A harmonized risk data architecture forms the basis for data-driven product innovations that can enable margin improvements of 5–10%.
• Optimized credit portfolio management: More precise risk assessments lead to improved pricing and lending decisions, which can increase net interest margins by 10–

20 basis points.

• Increased trading effectiveness: Real-time risk insights enable more agile trading decisions and can improve trading performance by 5–15%.
• Valuation multiples: Financial institutions with demonstrably superior risk data capabilities are rewarded by analysts and investors with higher valuation multiples, which directly impacts share price.

🔄 ADVISORI's ROI-oriented implementation approach:

• Business case development: We create a detailed business case with clearly quantified cost savings and value creation potential.
• ROI-based prioritization: We structure the BCBS‑239 roadmap so that high-value measures are implemented early and contribute positively to cash flow.
• Continuous performance measurement: Implementation of KPIs that make the financial impact of BCBS‑239 compliance transparent and continuously trackable.

How does the growing importance of AI and machine learning in risk management change the BCBS-239 compliance requirements for financial institutions?

The integration of AI and machine learning in risk management poses new fundamental challenges for the BCBS‑239 framework, as these technologies exponentially increase the complexity, speed, and opacity of risk data processes. At the same time, the convergence of BCBS‑239 and AI offers transformative opportunities for a new generation of data-driven risk management.

🔍 New dimensions of BCBS‑239 compliance through AI:

• Explainability and transparency: The black-box nature of many AI models creates fundamental governance challenges for the BCBS‑239 principle of traceability. New methods for model explainability (XAI) are required to meet regulatory requirements.
• Data quality as a limiting factor: AI systems amplify data quality problems exponentially. A robust BCBS‑239 data quality framework becomes a critical success factor for the effective use of ML in risk management.
• Model risk management: The complexity of ML models requires a substantial extension of the model risk framework under BCBS‑239, with new governance structures and validation processes for algorithmic decisions.
• Real-time capability: AI-based early warning systems require near-real-time data, raising BCBS‑239 requirements for data architecture and aggregation capacities to a new level.

🛠 ️ Convergence of BCBS‑239 and AI as a strategic enabler:

• Automated data quality assurance: AI-supported anomaly detection and automated data cleansing processes can enhance the efficiency and effectiveness of BCBS‑239 data quality controls.
• Predictive compliance: Predictive analytics can identify potential compliance issues before they lead to regulatory violations.
• Dynamic risk reporting: AI-driven risk cockpits enable adaptive, user-centric visualization of risk information that meets the requirements of various stakeholders.
• Self-learning data governance: ML algorithms can analyze data usage and access patterns and continuously optimize governance frameworks.

🚀 ADVISORI's forward-looking BCBS‑239 & AI approach:

• AI-ready data architecture: We develop BCBS‑239-compliant data architectures that are optimized from the ground up for the use of AI and ML.
• Explainable AI governance: Implementation of governance frameworks specifically designed to meet the transparency and traceability requirements of AI models in the regulated financial environment.
• Integrated model risk management: Development of extended MRM frameworks that cover both traditional statistical and modern ML models equally.
• Continuous learning loops: Establishment of feedback mechanisms that enable continuous improvements in both data quality and ML model performance.

How can we use BCBS-239 compliance as a catalyst for a comprehensive digital transformation of our risk management processes?

BCBS‑239 compliance should not be viewed in isolation, but as a strategic lever for a comprehensive digital transformation of risk management. A forward-looking implementation not only creates regulatory conformity, but establishes the foundations for a fully digitalized, data-driven risk management of the next generation.

💼 BCBS‑239 as a transformation catalyst:

• Data ecosystem transformation: BCBS‑239 provides the regulatory impetus for the fundamental redesign of fragmented data silos into an integrated, enterprise-wide risk data ecosystem that serves as the backbone of digital transformation.
• IT architecture modernization: The requirements for data integration and aggregation capabilities justify substantial investments in modern data platforms, cloud infrastructure, and API-based architectures that would otherwise be difficult to justify.
• Process automation: The standardization of data flows and data definitions under BCBS‑239 creates the prerequisites for end-to-end automation of risk processes and the elimination of manual interventions.
• Change management: BCBS‑239 projects create organizational readiness for change and data competency that is valuable far beyond the regulatory context for the entire digital transformation.

🖥 ️ Architectural building blocks of the transformation:

• Data mesh & data fabric: Implementation of domain-oriented, decentralized data architectures that enable both BCBS‑239 compliance and maximum organizational agility.
• Cloud-native risk platforms: Migration of legacy risk systems to scalable, cloud-based platforms that meet regulatory requirements while offering maximum technological flexibility.
• Real-time risk analytics: Building capabilities for real-time risk data aggregation and analysis that both comply with BCBS‑239 and unlock new business opportunities.
• Digital risk twins: Development of digital twins for risk scenarios that simulate complex interdependencies and enable a more precise understanding of risk cascades.

🌐 Organizational success factors of the transformation:

• Chief Data Officer as transformation leader: Positioning the CDO not only as the compliance officer, but as a strategic driver of the digital risk transformation.
• Agile delivery models: Implementation of agile, cross-functional teams that combine both regulatory expertise and digital capabilities.
• Digital risk competency: Development of new capability profiles at the intersection of risk management, data analytics, and digital technology.
• Innovation labs: Establishment of dedicated experimentation spaces where new digital risk management approaches can be tested within a BCBS‑239-compliant framework.

How does BCBS-239 influence the competitiveness of financial institutions in the context of increasing market consolidation?

BCBS‑239 is increasingly evolving from a regulatory requirement into a strategic differentiator and competitive factor in the consolidating financial industry. Institutions that view BCBS‑239 as a strategic opportunity can achieve significant advantages in intensified competition and strengthen their market position.

🌐 BCBS‑239 as a competitive factor in the consolidation phase:

• Acquisition potential and valuation premiums: Institutions with mature BCBS‑239 compliance are rewarded with significant valuation premiums in M&A transactions, as they offer lower post-merger integration risks and reduced regulatory uncertainty.
• Accelerated integration in mergers: A BCBS‑239-compliant data architecture enables significantly faster and more cost-effective integration of data assets in acquisitions and mergers – a critical success factor for value-creating M&A activities.
• Strategic flexibility for expansion: Institutions with robust risk data aggregation can enter new markets and business areas with lower operational risk and design their expansion strategies more flexibly.
• Attractiveness for strategic investors: A demonstrably advanced BCBS‑239 implementation signals to institutional investors a future-proof governance model and reduces risk premiums in company valuation.

🛡 ️ Defensive competitive advantages through BCBS‑239 excellence:

• Resilience to market shocks: Institutions with superior risk data aggregation can better absorb market volatility and adjust their positions more quickly and precisely during periods of stress.
• Reduction of regulatory capital add-ons: Full BCBS‑239 compliance can lead to significantly lower SREP add-ons, creating direct capital cost and RoE advantages over competitors.
• Improved credit ratings: Rating agencies are increasingly taking the quality of risk data management into account in their assessments, leading to more favorable refinancing conditions.
• Higher response speed: The ability to quickly aggregate precise risk data enables institutions to respond to regulatory changes and ad-hoc requests faster than their competitors.

💡 Offensive competitive advantages through BCBS‑239 as an innovation platform:

• Data-driven product innovation: A consistent, high-quality risk data base enables the development of innovative products with more precise pricing and risk differentiation.
• Superior client advisory: The ability to analyze consolidated client data in real time opens new dimensions in personalized advisory and relationship management.
• More efficient capital allocation: Improved risk measurement and aggregation leads to optimized capital allocation and higher returns on regulatory capital compared to competitors.
• Talent magnet effect: Institutions with advanced data architectures and analytical capabilities attract highly qualified data and risk specialists, who in turn reinforce the competency advantage.

How can we optimally design the organizational structure and governance processes for BCBS-239 compliance without sacrificing speed of innovation?

A forward-looking governance architecture for BCBS‑239 balances compliance requirements with agility and the capacity for innovation. ADVISORI develops organizational models that combine regulatory security with the dynamism required for digital competition and bring about a sustainable transformation of data culture.

🏛 ️ Principles of a future-proof BCBS‑239 governance:

• Federated governance instead of centralized control: Implementation of a federated governance model that defines clear overarching standards but empowers decentralized units to act agilely within these guardrails.
• Data product thinking: Reconceptualization of risk data as internal products with defined responsibilities, service levels, and customer journeys – analogous to external product development processes.
• Bimodal organization: Establishment of dual speeds with stable core processes for regulatory-critical data and agile structures for innovation areas and data analytics.
• Principle-based rather than rule-based governance: Focus on principles and outcomes rather than rigid rule catalogs, enabling flexibility in implementation without compromising regulatory objectives.

🔄 Transformative organizational models for BCBS‑239:

• Data mesh organization: Decentralization of data responsibility into domain-oriented teams with end-to-end ownership of their data products, while ensuring overarching governance principles.
• Hybrid center of excellence: Combination of a lean, strategic data governance CoE with embedded data stewards in the business units, acting as a bridge between central standards and decentralized implementation.
• DataOps teams: Cross-functional teams responsible for data quality, integration, and provisioning, applying DevOps principles to data management to combine speed with quality.
• Regulatory technology incubators: Dedicated teams at the intersection of compliance and technology that develop innovative RegTech solutions and integrate them into existing governance.

🚀 Process design for compliance and innovation:

• Continuous compliance through automation: Integration of compliance checks into automated data pipelines that continuously ensure and document adherence to BCBS‑239 requirements.
• Agile regulatory management: Adaptation of agile methods for the implementation of regulatory requirements with iterative releases and continuous improvement rather than large big-bang projects.
• Innovation sandboxes: Establishment of protected experimentation spaces where new approaches to data management and analytics can be tested without jeopardizing regulatory compliance.
• Regulatory testing as code: Implementation of automated tests for regulatory requirements that continuously ensure compliance already during the development phase of data models and processes.

What concrete steps should our board prioritize to achieve sustainable BCBS-239 compliance that goes beyond mere formal fulfillment?

Sustainable BCBS‑239 compliance requires a strategic commitment from the board that goes beyond isolated measures and compliance checklists. ADVISORI supports boards and supervisory bodies in initiating and accompanying a profound transformation of the risk data culture that combines long-term regulatory conformity with strategic added value.

🔝 Board-level priorities for sustainable BCBS‑239 excellence:

• From project to program: Transformation of BCBS‑239 compliance from a time-limited project to a permanent, strategic program with continuous further development and clear anchoring in the corporate strategy.
• Integrated target operating model: Development and implementation of a TOM for risk data management that brings together roles, responsibilities, processes, and technologies in a coherent framework.
• Executive accountability framework: Establishment of clear, personal accountability for BCBS‑239 compliance at board and senior management level, linked to compensation components and performance evaluation.
• Cultural transformation roadmap: Initiation of a comprehensive cultural transformation that anchors the importance of data quality and governance as a strategic value in the corporate culture.

📊 Strategic metrics for sustainable compliance:

• Development of a BCBS‑239 maturity model: Implementation of a multidimensional maturity model that goes beyond regulatory minimum requirements and makes continuous further development measurable.
• Balanced scorecard for risk data quality: Introduction of a balanced assessment methodology that covers both quantitative metrics (e.g., data quality rates) and qualitative dimensions (e.g., usability for decision-making processes).
• Benchmarking and peer comparison: Regular comparison with leading institutions and best practices to identify development potential and set ambitious but realistic targets.
• Value realization tracking: Systematic capture and assessment of the business value generated by improved risk data processes to justify ongoing investments.

💼 Change management and capability building:

• Executive education program: Development of a specific training program for top management that creates a deep understanding of the strategic importance of risk data management.
• Center of excellence: Establishment of a BCBS‑239 center of competence that acts as a catalyst for organization-wide transformation and disseminates best practices.
• Talent acquisition strategy: Targeted recruitment of specialists at the intersection of risk management, data analytics, and regulatory compliance, supplemented by upskilling of existing staff.
• Cross-functional collaboration model: Development and implementation of a model for effective collaboration between risk management, IT, compliance, and business units that overcomes siloed thinking.

What future regulatory developments in the area of risk data management should we anticipate in order to make our BCBS-239 investments future-proof?

The regulatory landscape in the area of risk data management is continuously evolving, with increasing requirements for granularity, integration, and real-time capabilities. A forward-looking BCBS‑239 strategy must anticipate these developments early in order to make compliance investments sustainable and avoid costly retrofitting.

🔮 Anticipated regulatory developments in risk data management:

• Integrated risk data framework: Consolidation of previously separate regulatory requirements (BCBS‑239, AnaCredit, BIRD, etc.) into a comprehensive, integrated framework for risk data management with standardized data definitions and granularity requirements.
• Near-real-time regulatory reporting: Increased requirements for the timely provision of risk data, with a gradual shift from monthly/quarterly cycles to weekly, daily, or even intraday reports for critical risk indicators.
• Extension to non-financial risks: Expansion of structured data collection and aggregation requirements to non-financial risk categories such as operational risks, compliance risks, and in particular ESG factors.
• Regulatory APIs and direct data access: Development towards standardized API interfaces that give supervisory authorities direct, automated access to defined risk data pools, replacing traditional report submissions.

🔍 Technological compliance trends for proactive adaptation:

• AI governance as an extension of BCBS‑239: New requirements for the governance, transparency, and validation of AI and machine learning models in risk management, extending BCBS‑239 principles with specific algorithm governance.
• Blockchain/DLT for regulatory reporting: Development of blockchain-based solutions for immutable, transparent regulatory reporting with automated validation and audit trail.
• Privacy-preserving analytics: New technologies such as federated learning and homomorphic encryption that enable privacy-compliant analyses without exposing sensitive data – particularly relevant for cross-border data aggregation.
• Quantum-resistant data security: Preparation for post-quantum cryptography to ensure the long-term security of sensitive risk data against future quantum computer-based attacks.

🛡 ️ ADVISORI's approach to future-proof BCBS‑239 compliance:

• Regulatory horizon scanning: Continuous monitoring and analysis of regulatory trends and drafts to identify adaptation needs at an early stage.
• Future-proof data architecture: Development of a data architecture that is inherently flexible and extensible to meet future regulatory requirements with minimal adjustments.
• Regulatory strategy wargaming: Simulation of various regulatory scenarios to identify vulnerabilities and develop proactive adaptation strategies.
• Regulatory change management capability: Establishment of a specialized organizational unit that identifies regulatory changes early, analyzes them, and translates them into concrete implementation requirements.

How can we master the balancing act between group-wide BCBS-239 standardization and local regulatory specificities in international banking groups?

Balancing global harmonization with local compliance is one of the greatest challenges in implementing BCBS‑239 within international banking groups. ADVISORI develops tailored governance models that combine group-wide efficiency with consideration of local specificities and meet regulatory requirements at all levels.

🌍 Principles of effective multi-jurisdiction governance:

• Global principles, local implementation: Development of a two-tier governance framework with binding group-wide principles and standards for data quality and governance, but flexible implementation modalities for local entities.
• Regulatory taxonomy mapping: Systematic mapping and harmonization of different regulatory requirements (ECB, Fed, FCA, FINMA, etc.) in an integrated regulatory mapping framework that identifies commonalities and resolves contradictions.
• Modular governance structure: Creation of flexible governance mechanisms that meet both the operational integration requirements of the group and local supervisory requirements.
• Proportionality principle: Differentiated implementation depth depending on the systemic relevance and size of the local entity, while maintaining global minimum standards.

🔄 Operational implementation models for international banking groups:

• Hub-and-spoke data governance: Central definition of data standards, methods, and tools by a group data office, combined with local data governance functions that ensure implementation and regulatory compliance on the ground.
• Federated data architecture: Implementation of a federated data architecture that combines local data sovereignty with central aggregation capability while taking into account regulatory data localization requirements.
• Matrix accountability model: Establishment of a dual reporting structure for local data officers who report both to local management and to central group data governance.
• Global-local alignment process: Structured process for coordination and continuous harmonization between global standards and local requirements, with clear escalation mechanisms in case of conflicts.

🛠 ️ Technological enablers for global harmonization:

• Global data dictionary with local extensions: Implementation of a central business glossary with the option of local adaptations and regulatory extensions, while ensuring traceability back to global definitions.
• Multi-jurisdiction lineage platform: Development of a cross-cutting data lineage solution that makes both local and global data flows transparent and traceably links the regulatory requirements of various jurisdictions.
• Harmonized data quality rules: Development of a multi-layered data quality architecture that combines global rules with local extensions and monitors them in an automated manner.
• Flexible reporting layer: Implementation of an adaptive reporting framework that can generate different regulatory formats from a consolidated data base.

What does successful collaboration between business and IT look like in BCBS-239 implementation in order to overcome siloed thinking?

Successful BCBS‑239 implementation requires a fundamental transformation of collaboration between business units and IT. ADVISORI supports financial institutions in breaking down traditional silos and establishing a new culture of collaborative data responsibility that combines regulatory compliance with operational excellence.

🤝 New paradigms of business-IT collaboration:

• Shared accountability model: Establishment of shared responsibilities for data quality and BCBS‑239 compliance between business units as data owners and IT as technical enablers, with clearly defined roles and shared KPIs.
• Data as a product, not an IT asset: Repositioning of risk data as strategic business products with defined quality characteristics, service levels, and customer segments, for which business and IT are jointly responsible.
• DevRegOps as an organizational principle: Integration of development, operations, and regulatory compliance in a continuous process that combines speed with regulatory security.
• Data-centric operating model: Transformation of the operating model away from functional silos towards data-centric, cross-functional teams with end-to-end responsibility for risk data products.

🔄 Organizational bridge structures:

• Data product owner as a key role: Establishment of a new hybrid role at the intersection of business and IT that combines deep subject matter expertise with technical know-how and is responsible for the end-to-end quality of risk data products.
• Federated center of excellence: Development of a distributed BCBS‑239 center of competence with representatives from business and IT that develops standards, disseminates best practices, and acts as a catalyst for organizational transformation.
• Collaborative governance boards: Implementation of joint governance bodies in which business and IT decide on data standards, processes, and architectures on equal footing.
• Cross-functional squads: Formation of permanent or temporary cross-functional teams for specific data domains or BCBS‑239 implementation tasks that work directly together rather than communicating across functional boundaries.

🧠 Fostering a shared data culture:

• Business data literacy program: Systematic strengthening of data competency in business units, particularly in risk management and finance, to understand technical concepts and internalize the importance of data quality.
• IT business acumen development: Targeted promotion of understanding of business processes and risk management concepts in IT, to align technology decisions with business requirements.
• Shared OKRs and incentives: Development of cross-functional objectives and key results (OKRs) for BCBS‑239 compliance that feed into the performance evaluation of both business and IT leaders.
• Collaborative innovation workshops: Regular joint workshops to develop innovative solutions for BCBS‑239 challenges that bring together technological possibilities and subject matter requirements.

What cloud strategies enable cost-efficient BCBS-239 compliance while taking into account the special security requirements for risk data?

Cloud transformation offers financial institutions unique opportunities to make BCBS‑239 compliance more cost-efficient and scalable. At the same time, handling sensitive risk data requires special security concepts. ADVISORI supports the development of future-proof cloud strategies that meet regulatory requirements while leveraging the benefits of modern cloud technologies.

☁ ️ Strategic cloud approaches for BCBS‑239 compliance:

• Hybrid cloud strategy with risk data classification: Development of a differentiated model that decides, based on data classification and regulatory requirements, which risk data is processed in public cloud, private cloud, or on-premises.
• Cloud-native risk data platforms: Use of cloud-native platforms for risk data aggregation and reporting that offer inherent scalability, elasticity, and pay-per-use models, synchronizing costs with actual demand.
• Multi-cloud approach for resilience: Avoidance of vendor lock-in and increased fault tolerance through targeted distribution of risk data workloads across multiple cloud providers while maintaining a unified governance framework.
• Containerization of risk data processes: Use of containerization and Kubernetes for the standardization, portability, and consistent execution of risk data processes across different environments.

🔒 Cloud security for risk data and regulatory compliance:

• Defense-in-depth for cloud risk data: Implementation of a multi-layered security model with measures at the network, identity, data, and application levels, taking into account the special protection requirements of risk data.
• Zero-trust architecture: Consistent application of the zero-trust principle with continuous authentication and authorization, granular access rights, and full encryption for all risk data.
• Sovereign cloud services: Use of sovereign cloud services for particularly sensitive risk data that meet specific legal requirements regarding data localization, access control, and governmental access.
• Continuous security testing: Implementation of automated, continuous security tests for cloud-based risk data infrastructures to identify and remediate vulnerabilities at an early stage.

📊 Cloud-specific governance for BCBS‑239:

• Cloud data lineage: Extension of existing data lineage solutions with cloud-specific components that create transparency over data flows between on-premises and various cloud environments.
• API-based governance: Use of API management platforms to control and monitor data exchange between various cloud services and on-premises systems.
• Cloud FinOps for risk data: Implementation of FinOps processes that make the costs of cloud-based BCBS‑239 compliance transparent and optimize them, with clear allocation to business functions.
• Regulatory compliance as code: Automated monitoring and documentation of BCBS‑239 compliance in cloud environments through policy-as-code and continuous compliance checks in the CI/CD pipeline.

How can we use BCBS-239 compliance as a starting point for a comprehensive ESG data strategy?

The growing importance of Environmental, Social, and Governance (ESG) factors for the risk management of financial institutions creates synergies with existing BCBS‑239 initiatives. An integrated strategy makes it possible to use the data capabilities developed for BCBS‑239 as a foundation for a robust ESG data strategy, thereby combining regulatory compliance with sustainable competitiveness.

🔄 Synergies between BCBS‑239 and ESG data requirements:

• Common governance principles: The BCBS‑239 governance principles for risk data – such as clear ownership, quality controls, and end-to-end lineage – are directly transferable to ESG data management and form a solid basis for integration.
• Parallel aggregation challenges: Like traditional risk data, ESG data requires the aggregation of heterogeneous, often external data sources with varying quality and granularity – capabilities already developed for BCBS‑239.
• Complementary reporting requirements: Both BCBS‑239 and ESG reporting require the ability to aggregate granular data for various stakeholders and report at different time intervals.
• Integrated risk perspective: The increasing integration of ESG factors into traditional risk categories (credit, market, operational risks) requires a consolidation of the data base that can benefit from an existing BCBS‑239 infrastructure.

📊 Extension of the BCBS‑239 architecture for ESG data:

• Extended data models: Enrichment of existing risk data models with ESG-specific attributes and entities that enable an integrated view of traditional and sustainability-related risks.
• Alternative data integration: Extension of the data architecture with capabilities for integrating alternative data sources (satellite data, social media, NGO reports) relevant to ESG assessments.
• Advanced analytics layer: Implementation of specialized analytics functions for ESG data that build on the foundational BCBS‑239 data aggregation and can capture complex sustainability relationships.
• Unified reporting framework: Development of an integrated reporting framework that presents both traditional risk metrics and ESG KPIs in consolidated dashboards for various decision-making levels.

🌱 Strategic advantages of an integrated BCBS‑239/ESG data strategy:

• Regulatory synergies: Preparation for upcoming ESG-related regulations (e.g., EU Taxonomy, SFDR, extended stress tests) by leveraging existing BCBS‑239 compliance capabilities.
• Efficiency gains: Avoidance of parallel data infrastructures and processes by integrating ESG data management into existing BCBS‑239 frameworks, leading to significant cost savings.
• Improved decision-making: Creation of a comprehensive view of risks by integrating traditional and ESG-related risk factors in a unified data model.
• Competitive differentiation: Positioning as a pioneer in sustainable finance through superior ESG data analytics capabilities, built on a robust BCBS‑239 foundation.

How can we optimally synchronize our BCBS-239 compliance measures with the digital transformation of our bank?

Synchronizing BCBS‑239 compliance with digital transformation offers unique synergy potential. Rather than running two parallel initiatives, ADVISORI supports the integration of both transformation programs to realize efficiency gains and create sustainable strategic value.

🔄 Strategic synchronization points:

• Common data architecture vision: Development of a unified target architecture that takes into account both the requirements of digital transformation (agility, customer focus, innovation) and BCBS‑239 compliance (governance, quality, lineage).
• Harmonized transformation roadmap: Integration of BCBS‑239 milestones into the overarching digital transformation roadmap to identify dependencies and define optimal implementation sequences.
• Consolidated stakeholder management: Development of an integrated approach for the involvement of business units, IT, and compliance that minimizes change management effort and ensures consistent communication.
• Shared value tracking: Establishment of a cross-cutting value tracking framework that measures and makes transparent both the regulatory compliance value and the business transformation value.

💡 Technological levers for integrated transformation:

• API-first strategy: Implementation of an API-driven architecture that enables both the agility of digital innovations and the structured governance of risk data.
• Metadata-driven development: Use of extended metadata frameworks that can be used both for documenting regulatory requirements and for developing digital services.
• Event-driven architecture: Implementation of an event-driven architecture that connects real-time data requirements of digital channels with regulatory aggregation requirements.
• Low-code/no-code platforms: Use of low-code platforms for governance workflows and reporting solutions that enable rapid adaptation to regulatory changes without burdening core IT development.

👥 Organizational integration for maximum synergies:

• Digital & regulatory transformation office: Creation of an integrated steering unit that coordinates both transformation programs and systematically identifies and captures synergies.
• Dual-purpose teams: Assembly of cross-functional teams that can competently implement both digital innovations and regulatory compliance requirements.
• Integrated portfolio management: Establishment of a portfolio-based prioritization approach that equally considers regulatory requirements and digital innovations and allocates resources optimally.
• Capabilities-based operating model: Development of a capabilities-based operating model that bundles both digital and regulatory competencies in integrated teams rather than isolating them in separate organizational units.

How can we use the implementation of BCBS-239 to elevate our entire risk management to a new level?

BCBS‑239 offers a unique opportunity beyond pure compliance to fundamentally transform risk management. ADVISORI supports financial institutions in using BCBS‑239 as a catalyst for a quantum leap in risk management that leads to superior decision-making capability and sustainable competitive advantage.

📈 Strategic levers for risk management transformation:

• From reporting to real-time risk intelligence: Transformation of traditional periodic risk reporting into real-time risk intelligence that enables proactive decisions and dramatically shortens response times to market changes.
• From compliance to competitive edge: Repositioning of risk management from a compliance function to a strategic enabler that creates competitive advantages in pricing, capital allocation, and strategic decisions through superior risk information.
• From risk avoidance to risk-return optimization: Development of analytical capabilities that go beyond pure risk measurement and enable an optimal balance between risk and return, based on a granular and timely data base.
• From risk control to risk culture: Democratization of risk data and insights across the entire organization to establish a data-driven risk culture in which every employee can make well-informed risk decisions.

🔍 New risk management capabilities through BCBS‑239:

• Dynamic limit management: Implementation of a dynamic, data-driven limit management system that can automatically respond to changes in the market environment or risk profile, based on improved aggregation capabilities.
• Predictive risk analytics: Use of the consolidated data base created by BCBS‑239 for the development of predictive risk models that identify potential problems early and enable proactive action.
• Scenario-based decision support: Development of capabilities for the rapid execution of complex risk scenarios based on aggregated data, giving decision-makers a deeper understanding of the potential impact of various options.
• Risk-adjusted performance management: Integration of granular risk information into performance measurement and compensation systems to create incentives for risk-conscious behavior at all levels.

🌐 Overarching changes in the risk operating model:

• Establishment of a risk data science center: Creation of a specialized team that applies advanced analytical techniques to the risk data base improved by BCBS‑239 and generates new insights for the business.
• Transformation of the risk operating model: Redesign of the risk operating model with a clear separation between factory functions (data collection, processing) and value-add functions (analysis, advisory), to maximize efficiency and strategic impact.
• Risk innovation lab: Creation of a dedicated innovation unit in risk management that tests new technologies and methods and evaluates their potential for the further development of risk management.
• Chief Risk Data Officer: Establishment of a specialized leadership role at the intersection of data management and risk management, responsible for the continuous development of risk data capabilities and maximizing strategic value.

What concrete metrics and KPIs should we implement to make the progress and success of our BCBS-239 implementation transparent?

Effective management of a BCBS‑239 implementation requires a differentiated measurement system that quantifies both compliance progress and business value. ADVISORI develops tailored measurement frameworks that create transparency, inform decisions, and make the ROI of BCBS‑239 investments demonstrable.

📊 Multidimensional metrics for comprehensive transparency:

• Compliance maturity metric: Development of a multidimensional maturity model that measures progress in implementing the BCBS‑239 principles on a 5-point scale for various risk categories, data domains, and organizational units.
• Data quality scorecard: Implementation of a granular scoring system for risk data quality with metrics for completeness, accuracy, timeliness, consistency, granularity, and availability – both at an aggregated and detailed level.
• Process efficiency KPIs: Measurement of the efficiency of risk data processes through metrics such as time-to-report, manual interventions, error rates, processing times, and process costs, with clear benchmarks against the baseline.
• Business value metrics: Quantification of business value through indicators such as reduction of regulatory capital add-ons, time and cost savings in reporting, improved decision-making speed, and quality improvements in risk management.

🎯 Strategic KPI framework for various stakeholders:

• Executive dashboard: Consolidated overview for the board and supervisory body with strategic KPIs on BCBS‑239 compliance, critical risks, resource deployment, and realized business value, presented in an intuitive traffic light system.
• Operational scorecard: Detailed metrics for middle management that track progress at the operational level, identify bottlenecks, and support resource allocation decisions.
• Team-level metrics: Granular, activity-related metrics for project and implementation teams that guide daily prioritization and promote continuous improvement.
• Regulatory reporting: Structured metrics for communication with supervisory authorities that make progress transparent and strengthen confidence in the implementation.

📱 Innovative measurement methods for continuous improvement:

• Continuous compliance monitoring: Implementation of automated monitoring systems that capture BCBS‑239 compliance metrics in real time and proactively generate alerts in the event of deviations.
• Predictive implementation analytics: Use of predictive analytics to identify potential delays or quality issues early and take corrective action before they become critical.
• Peer benchmarking: Systematic comparison of own BCBS‑239 metrics with industry averages and best-in-class performers to identify improvement potential and set ambitious targets.
• Adaptive KPI evolution: Continuous further development of the measurement system throughout the implementation to integrate new insights and ensure ongoing relevance for steering purposes.

How can we sustainably optimize the costs of BCBS-239 implementation without jeopardizing quality and compliance?

Cost-efficient BCBS‑239 implementation requires a strategic balance between compliance requirements, quality objectives, and resource deployment. ADVISORI supports financial institutions in developing a sustainable cost optimization approach that combines long-term efficiency with regulatory conformity and avoids waste without incurring compliance risks.

💰 Strategic cost optimization levers:

• Prioritization by risk-benefit ratio: Implementation of a structured prioritization process that identifies and focuses on the most critical risk data domains based on regulatory significance, data quality gaps, and business impact.
• Phased implementation approach: Development of a staged implementation approach that realizes quick wins with high ROI early and distributes cost-intensive measures over a longer period without jeopardizing regulatory deadlines.
• Synergy potential with other initiatives: Systematic identification and use of synergies with parallel projects such as GDPR compliance, digital transformation, or IT modernization to avoid duplication of effort and share investments.
• Balanced buy-vs-build strategy: Development of a balanced strategy for make-or-buy decisions regarding BCBS‑239 tools and solutions, taking into account total cost of ownership, flexibility, and strategic fit.

🛠 ️ Operational efficiency measures:

• Automation first principle: Consistent prioritization of the automation of manual processes in data quality controls, lineage documentation, and reporting, with a focus on repetitive, high-volume tasks.
• Standardization of implementation patterns: Development of reusable patterns and components for common BCBS‑239 implementation tasks that reduce development effort and ensure quality through consistency.
• Agile delivery with minimum viable compliance: Application of agile methods with the concept of 'minimum viable compliance', which initially meets regulatory minimum requirements and is then iteratively extended, avoiding over-delivery in early phases.
• Managed services for standard functions: Outsourcing of standardized BCBS‑239 functions such as data quality controls, report generation, or lineage documentation to specialized service providers with economies of scale.

🧠 Organizational and cultural efficiency factors:

• Skills-based resource allocation: Precise assignment of staff to BCBS‑239 tasks based on their specific skills and experience to minimize learning curves and maximize productivity.
• Knowledge management platform: Development of a central knowledge base for BCBS‑239 implementation that documents and disseminates best practices, lessons learned, and reusable assets.
• Cross-training and skill development: Targeted training of staff in regulatory, technical, and methodological aspects to reduce dependency on external consultants and build internal capacity.
• Incentives for efficiency improvement: Introduction of incentive systems that promote continuous process improvement and cost awareness in BCBS‑239 implementation without compromising compliance objectives.

How can we use the experience gained from BCBS-239 to prepare for future regulatory requirements?

The BCBS‑239 implementation provides valuable experience and capabilities that can be used as a strategic foundation for addressing future regulatory requirements. ADVISORI supports financial institutions in systematically leveraging these experiences and building a forward-looking regulatory change management capability.

🔮 Transferable experiences from BCBS‑239:

• Requirements analysis methodology: The approaches developed for BCBS‑239 for interpreting principles-based regulation and translating it into concrete technical and organizational requirements are transferable to new regulatory initiatives.
• Data governance frameworks: The governance structures and processes implemented for BCBS‑239 form a robust basis for integrating new data requirements from future regulations.
• Cross-functional collaboration: The experience of collaboration between business units, IT, risk management, and compliance creates a model for effectively addressing future regulatory challenges.
• Implementation methodology: The lessons learned from the BCBS‑239 implementation – from requirements analysis through architecture decisions to testing – form best practices for future regulatory projects.

🛡 ️ Building regulatory resilience and agility:

• Modular compliance architecture: Development of a flexible, modular data and process architecture that can integrate new regulatory requirements with minimal adjustments.
• Regulatory change management framework: Establishment of a structured process for the early identification, analysis, and prioritization of new regulatory requirements with clear responsibilities and escalation paths.
• Regulatory knowledge management: Development of a central knowledge base and community of practice for regulatory expertise that promotes continuous learning and ensures knowledge transfer between different regulatory projects.
• Regulatory technology radar: Implementation of systematic monitoring for new RegTech solutions that can support the management of future regulatory requirements.

🚀 Strategic levers for future regulations:

• From point solution to compliance platform: Evolution of the BCBS‑239 infrastructure into a comprehensive compliance platform that serves as a foundation for various current and future regulatory requirements.
• Proactive regulatory engagement: Use of the expertise gained through BCBS‑239 to actively participate in consultations and influence the design of future regulations in dialogue with supervisory authorities.
• Compliance by design: Integration of regulatory requirements into the earliest phases of product development and system design to minimize subsequent adjustments.
• Regulatory horizon scanning: Development of a systematic early warning system for new regulatory developments that identifies potential implications early and enables strategic adaptation.

How can we most convincingly demonstrate the success of our BCBS-239 implementation to supervisory authorities?

Convincingly demonstrating BCBS‑239 compliance to supervisory authorities requires more than the formal fulfillment of regulatory requirements. ADVISORI supports financial institutions in conducting an evidence-based, traceable, and trust-building dialogue with supervisory authorities, characterized by concrete evidence and strategic communication.

📋 Evidence-based compliance demonstration:

• Multilayer evidence framework: Development of a multi-tiered evidence concept that demonstrates compliance at various levels – from a highly aggregated board-level view to granular technical details, depending on the audience and audit focus.
• Automated compliance documentation: Implementation of automated mechanisms for continuous documentation of BCBS‑239 compliance, making data quality controls, lineage information, and governance processes transparent and traceable.
• Quantitative progress measurement: Establishment of objective, quantitative metrics for measuring implementation progress and compliance quality, enabling a fact-based discussion with supervisory authorities.
• Independent validation: Conduct of regular independent validations of BCBS‑239 compliance by internal or external auditors, whose results are proactively shared with supervisory authorities.

🤝 Strategic dialogue with supervisory authorities:

• Proactive communication strategy: Development of a structured approach for continuous, transparent dialogue with supervisory authorities that goes beyond pure compliance reporting and addresses strategic aspects of the risk data architecture.
• Executive sponsorship: Active involvement of board and senior management in exchanges with supervisory authorities to demonstrate the institution's commitment to BCBS‑239 compliance.
• Transparent issue management: Open communication of existing challenges and planned measures, accompanied by clear timelines and responsibilities – an approach that builds trust and avoids defensive communication.
• Contextual implementation story: Presentation of the BCBS‑239 implementation in the context of the institution's overarching risk management and data strategies, to highlight the strategic value beyond pure compliance.

🔍 Compelling evidence for supervisory authorities:

• Functional demonstration rather than documentation: Supplementing written documentation with live demonstrations of implemented capabilities, e.g., through walk-throughs of end-to-end data processes or demonstrations of governance workflows.
• Real-world stress testing: Conduct and documentation of realistic stress tests that demonstrate the resilience and functionality of the implemented BCBS‑239 solutions under stress conditions.
• User adoption evidence: Demonstration of the actual use and integration of BCBS‑239 solutions into the daily working processes of risk management through usage statistics, user feedback, and concrete use cases.
• Continual improvement mechanism: Demonstration of an established process for the continuous improvement of BCBS‑239 compliance that responds to supervisory feedback, internal insights, and changing business requirements.

How can we as an institution benefit from the risk data improved through BCBS-239 in other business areas as well?

The improved risk data resulting from BCBS‑239 holds considerable value potential beyond compliance and risk management. ADVISORI supports financial institutions in strategically leveraging these high-quality data assets and realizing broader business value from the investments made.

💼 Cross-functional use potential:

• Sales and client management: Use of refined risk data for more precise client segmentation, personalized offer creation, and risk-adjusted pricing that can improve both profitability and client acquisition.
• Treasury and asset-liability management: Integration of granular risk information into liquidity and balance sheet management processes for optimized capital allocation, improved collateral management, and more efficient refinancing.
• Strategic planning and M&A: Use of consolidated risk data for well-founded strategic decisions, more accurate due diligence in acquisitions, and more precise valuation of business units or portfolios.
• Product development and innovation: Use of detailed risk data to develop innovative financial products with an optimized risk-return profile and better market differentiation.

🔄 Enablement strategies for broader data use:

• Self-service analytics: Implementation of user-friendly self-service analytics tools that enable business users in various departments to use BCBS‑239-compliant risk data for their specific use cases.
• Democratized risk insights: Development of intuitive dashboards and visualizations that make complex risk information accessible and actionable for various user groups.
• Integrated customer view: Enrichment of the 360-degree customer view with risk data from the BCBS‑239 data base to enable a comprehensive understanding of customer behavior, profitability, and potential.
• API-based data provisioning: Creation of an API layer that enables controlled access to BCBS‑239-compliant risk data for various applications and business processes without compromising data integrity.

📊 Innovative use cases beyond compliance:

• Predictive customer behavior modeling: Combination of risk data with other customer data for the development of predictive models that forecast customer behavior, churn risks, or cross-selling potential.
• Dynamic pricing optimization: Use of granular risk information for dynamic, risk-adjusted pricing that optimizes both competitiveness and profitability.
• Ecosystem risk intelligence: Provision of aggregated risk information for partners in the financial ecosystem (e.g., InsurTechs, payment service providers) to enable value-added services and unlock new revenue streams.
• Sustainable finance offerings: Use of extended risk data capabilities to integrate ESG factors into financial products and services that address growing customer needs in the area of sustainable investments.

How should a board strategically govern the long-term governance and resource deployment for BCBS-239?

Long-term strategic governance of BCBS‑239 requires a balanced governance model that aligns regulatory requirements with business priorities. ADVISORI supports boards and governing bodies in developing a sustainable steering approach that ensures compliance while maximizing the strategic value of investments.

🏛 ️ Strategic governance framework:

• Integrated governance model: Development of a comprehensive governance framework that positions BCBS‑239 not as an isolated compliance topic, but as an integral component of the overarching data and risk strategy.
• Board-level ownership: Clear anchoring of BCBS‑239 responsibility at board level with explicit assignment to a board member (typically CRO or CDO), supported by regular reporting to the full board.
• Balanced scorecard approach: Implementation of a balanced metrics system for the board level that makes both compliance aspects and the business value of BCBS‑239 investments transparent.
• Integrated risk and compliance committee: Establishment of a cross-cutting body that considers BCBS‑239 in the context of other regulatory and risk management initiatives and identifies synergies and dependencies.

📈 Sustainable resource allocation:

• Multi-year investment planning: Development of a multi-year investment strategy for BCBS‑239 that takes into account both ongoing maintenance costs and strategic further development, harmonized with the overarching IT and data budget.
• Capex-to-opex transition: Strategic transition from project-based investments (capex) to sustainable operational structures (opex) with clear responsibilities in the line organization.
• Dynamic resource allocation: Implementation of a flexible resource allocation model that can respond to regulatory changes, business priorities, and technological developments without jeopardizing fundamental compliance.
• Investment synergies: Systematic identification and use of synergies between BCBS‑239 investments and other strategic initiatives such as digital transformation, data analytics, or cloud migration.

🔄 Evolutionary operating model:

• Maturity-based operating model: Development of an adaptive operating model for BCBS‑239 that evolves with increasing maturity from a project-driven to a line-organization-integrated governance.
• Automation strategy: Strategic prioritization of the automation of manual BCBS‑239 processes to reduce long-term operating costs while improving quality and consistency.
• Capability development planning: Long-term planning for the development of internal capacities and competencies that enable sustainable BCBS‑239 compliance with reduced dependency on external consultants.
• Innovation budget: Allocation of dedicated resources for the exploration and testing of innovative technologies (such as AI, blockchain, or cloud-native solutions) that can make BCBS‑239 compliance more efficient or effective.

Success Stories

Discover how we support companies in their digital transformation

Generative KI in der Fertigung

Bosch

KI-Prozessoptimierung für bessere Produktionseffizienz

Fallstudie
BOSCH KI-Prozessoptimierung für bessere Produktionseffizienz

Ergebnisse

Reduzierung der Implementierungszeit von AI-Anwendungen auf wenige Wochen
Verbesserung der Produktqualität durch frühzeitige Fehlererkennung
Steigerung der Effizienz in der Fertigung durch reduzierte Downtime

AI Automatisierung in der Produktion

Festo

Intelligente Vernetzung für zukunftsfähige Produktionssysteme

Fallstudie
FESTO AI Case Study

Ergebnisse

Verbesserung der Produktionsgeschwindigkeit und Flexibilität
Reduzierung der Herstellungskosten durch effizientere Ressourcennutzung
Erhöhung der Kundenzufriedenheit durch personalisierte Produkte

KI-gestützte Fertigungsoptimierung

Siemens

Smarte Fertigungslösungen für maximale Wertschöpfung

Fallstudie
Case study image for KI-gestützte Fertigungsoptimierung

Ergebnisse

Erhebliche Steigerung der Produktionsleistung
Reduzierung von Downtime und Produktionskosten
Verbesserung der Nachhaltigkeit durch effizientere Ressourcennutzung

Digitalisierung im Stahlhandel

Klöckner & Co

Digitalisierung im Stahlhandel

Fallstudie
Digitalisierung im Stahlhandel - Klöckner & Co

Ergebnisse

Über 2 Milliarden Euro Umsatz jährlich über digitale Kanäle
Ziel, bis 2022 60% des Umsatzes online zu erzielen
Verbesserung der Kundenzufriedenheit durch automatisierte Prozesse

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