Credentials

Development of a Risk framework
Insingergilissen was aiming to quantify the COSO ERM framework into an easily displayed benchmarked risk curve. The focus lies here on the implementation of risk in the development of strategy in the search for performance. For our research, we used data from international banks with diverse business models. The objective was to achieve a risk curve focused on significant risk indicators like Asset under Management, CET1, LCR, and Loan-to-deposit ratio with which we find a relationship between Asset under Management growth as a performance indicator versus CET1, LCR, and loan-to-deposit ratio as risk indicators.

Support on ICAAP and ILAAP
Due to the merger of Insinger and Theodore Gilissen the department of Risk Management of Theodore Gilissen had to set up some extra activities. DRS supported Insingergilissen in their ICAAP and ILAAP process and other risk management activities. A junior business analyst of DRS worked on these activities for several months under the guidance of Michiel Hopman.

COFRA Holding coordinates the global business of the Brenninkmeijer family. It is active in the fields of retail, real estate, asset management and private equity. DRS supported various entities of the COFRA Holding in the field of Risk Management. Examples are ICAAP, Risk Appetite Framework, Operational Risk and improving the integrated risk management framework.

DRS supported de Volksbank on various Data and Risk topics:

  • IRRBB reporting: Assessment which coding language fits best for the conversion of the complex Excel files (IRRBB reporting): Matlab, Python or R. Rutger Lit investigated this part and provided the ALM department with an advise;
  • Converting complex Excel calculation and reporting files (IRRBB) into Matlab. Rutger Lit supported on this project together with Roel Gort, a Master student Econometrics with excellent coding skills;
  • Review of the mortgage prepayments model
  • Support on IRRBB regarding the new Guidelines on the management of interest rate risk arising from non-trading book activities
  • Support on the development of the Recovery Plan
  • Support on Resolution activities
  • Probability of Default forecasting;
    Based on a GEMs dataset and actual model, DRS developed new forecasting PD models for different asset portfolios. DRS provided FMO with a plan of approach for modelling calibrations and documentation.
  • Currency devaluation;
    We assessed the possibilities to add a factor that looks at the risk of local currency devaluation compared to mainly the US dollar and / or Euro (so-called hard currencies). This is a potential risk factor as in some cases the financial institutions we finance have direct or indirect currency risk. We have assessed the historic predictive value of HIS Markit Indicator, assessing if HIS Markit indicator is an appropriate benchmark to predict currency value.
  • Liquidity outflow rates;
    A key aspect of running a bank’s balance sheet is to ensure there are sufficient liquid means (i.e. cash or cash-equivalents) available at any time to fulfil all financial obligations of the company. A common method is to model future cash-flows based on historic trends. As risk managers are not only interested in the base case, these models should also provide a reliable estimate for stressed conditions. We assessed which variables are relevant for determining the outflow rate, and allocate these to commitment types, A 30-day outflow rate is forecasted in bases case and stressed.
  • Liquidity prepayment rates;
    A key aspect of running a bank’s balance sheet is to ensure there are sufficient liquid means (i.e. cash or cash-equivalents) available at any time to fulfil all financial obligations of the company. Some cashflows are uncertain because they depend on client behaviour like early repayment of a loan. We identified which variables are relevant for determining the pre-payment behaviour on portfolio level and allocate these to commitment types. Based on this information a base case term structure is developed, and stressed.
  • Macro analysis on loan performance:
    We analysed the impact of GDP variation in FMO’s investment portfolio performance (NPL and defaults). Moreover, we analysed this correlation for different sectors and industries given the share of each sector in GDP variation. We assessed the historical value of GDP variation in the performance results of the investment portfolio of FMO. Next to this we analysed if other macro-economic factors have higher predictive value than GDP.

Prediction of mortality rates
Provisum is the company pension fund for C&A Netherlands. We assessed if the mortality rate of Provisum deviates from the overall Dutch mortality rates provided on an annual basis by “Het Actuarieel Genootschap” (AG). Pension funds use correction factors on these AG rates based on there on client information. We assessed these correction factors using k-prototypes clustering and regression prediction models.

BNG bank (Bank Nederlandse Gemeenten: Development of a forecasting model in Matlab for credit spreads of corporates and governmental bonds. The objective was to gain more insight in volatility and possible downward risks in the portfolios.

Support on IRRBB. Assessment and review of the new Guidelines on the management of interest rate risk arising from non-trading book activities and assistance in improving the IRRBB framework.