Quantitative Finance (IFRS 9, IRB, Scoring)

In an increasingly demanding regulatory environment, and faced with the increasing volatility of the markets, the banks have since the financial crisis a strong need to equip themselves internally with calculation and modeling the risks to which they are exposed.

SUBMIT REQUEST FOR PROPOSAL

The financial crisis of 2008 revealed a weak resilience of banks and other market participants faced with a brutal deterioration of the economic situation. In order to overcome this fragility in a stressed environment, the regulatory framework as well as the accounting standards have evolved considerably, becoming more and more demanding.

By supporting banking institutions in the implementation of these requirements, we have implemented a proven approach adapted to each step of setting up a risk measurement and management system.

Thus, we offer to assist you in setting up:

Modelling - Mazars consultants develop a wide range of models for financial institutions, allowing you to assess and monitor credit risk. Models are driven on both the internal and external data.

Analytics and Research - Our Quant team can perform all types of analysis in the field of credit risk management. We employ a wide range of methods for risk analysis, starting from basic econometric methods to state-of-the-art machine learning and artificial intelligence algorithms. 

Training - Mazars consultants train clients to develop models for assessing credit risk components. We are glad to provide you with a key set of analytical and practical tools so you can independently develop models in Excel, MatLab, Python and R.

IFRS 9 compliance:

Mazars Russia has in-depth knowledge and experience in IFRS 9 implementation projects. Developing tailor-made methodologies and calculation tools (both on-premise and cloud) for:

  • Staging;
  • Segmentation of the portfolio;
  • Transition matrices assessment;
  • TTC (through-the-cycle) and PIT (point-in-time) probability of default (PD);
  • TTC and PIT loss given default (LGD);
  • Exposure at default modeling. 

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