Risk Advisory

We have brought together professionals with specialized skills in
methodological and modeling fields within the cutting-edge Risk Advisory Practice, aiming to provide comprehensive service to our clients. We leverage the agility and flexibility of a Solution Consulting company on one hand, and the informational assets, data ecosystem, and technological innovation of Cerved on the other.

We offer banks and financial companies an end-to-end approach in credit risk management, covered by the following services:

 

Model Development
We develop models for quantifying PD, LGD, and CCF parameters from a regulatory perspective (AIRB) and for impairment calculation (IFRS9), providing operational and methodological support, including incorporating regulatory updates into the models.

 

Model Validation
We support Control Functions (Internal Validation and Audit) in model design verifications, backtesting activities for estimated models (or model changes) on AIRB and IFRS9 parameters, and in constructing “benchmark” models based on advanced analytics approaches. We have expertise in designing validation frameworks and adapting them to regulatory changes.

 

Analytics & Risk Data
We have developed cross-functional capabilities allowing us to provide services and support in optimizing data transformation processes, as well as engineering and optimizing calculation processes within specific credit lifecycle activities (e.g., second level credit controls). All of this is achieved by leveraging innovative technologies and advanced analytics models.

We support Risk Management in integrating ESG risks into credit risk measurement models, satellite models, and Stress Tests, leveraging Cerved’s extensive information assets and ESG scores. The leadership role of the Cerved Group in providing scores for climate risk management and ESG assessments allows us to offer distinctive solutions in the market with end-to-end green solutions, particularly:

 

Integration of Climate Risks into Credit Risk Measurement Models
We propose methodological solutions for integrating climate/ESG risks into PD and LGD parameters through precise analysis and portfolio mapping regarding physical and transition risks, aiming to measure the correlation between climate/ESG risks and credit worthiness. In this context, we also propose approaches for evaluating impacts on credit monitoring and lending processes (e.g., through integration solutions with PEF and Early Warning systems).

 

Integration of Satellite Models
With our modeling expertise and scenario analyses from our research department, we offer solutions to assess the impact of climate risks on projections of PD and LGD parameters for ECL calculations, leveraging our supply of macroeconomic and financial data and KPIs.

 

Integration into the Risk Governance Framework
The solutions we propose for integrating climate risks into satellite models can also be adapted for regulatory Stress Test exercises and for ICAAP/ILAAP purposes, modeling sector-level impacts of ecological transition on key drivers feeding predictions on RWA and capital.

 

 

Thanks to our cross-functional expertise, we are able to provide support to our clients in solutions related to the world of Risk Governance, not only from the perspective of identifying strategies and risk limits (RAF) and measuring second Pillar risks (ICAAP, ILAAP) but also specifically addressing Stress Test and Model Risk Management issues.

 

Stress Test
For stress tests, we offer our clients a simulation platform to assess impacts on capital metrics (RWA, ECL), margins, and risk costs, leveraging our scenarios and econometric models. Through navigation dashboards, users can visualize the impact on these metrics under assumptions of future changes in PD and LGD, assuming a static scenario (base simulation) and dynamic balance-sheet assumptions / ability to modify underlying assumptions in dynamic simulation.

 

Model Risk Management
We have designed and developed a Model Risk Management framework that not only allows for an inventory of all models developed within the bank but also manages their lifecycle according to priority levels guided by various logics and drivers (e.g., nature of capital impacts, methodological complexity, etc.).