We help banks to design, implement and validate quantitative models to better identify and monitor risks arising from trading book activities. Our modeling experts support banks in satisfying regulatory requirements, building best-in-class internal models and developing analytics to ensure risks can be easily managed.
Our experience covers the full spectrum of traded risk modeling, including Market Risk, Counterparty Credit Risk, XVA and Margin Models.
When markets change at unprecedented speeds, gains and losses in your trading book can have a significant impact on financial fitness. Zanders’ approach to risk combines sophisticated data science with regulatory knowledge and market experience. In short, you can rely on us to bring a sense of balance and pragmatism to how you manage risks emerging from adverse market fluctuations.
We assist clients in developing new models or enhancing existing models to capture additional risks, reach regulatory requirements or to run more accurately and efficiently.
Our consultants support the implementation and testing of new models, usually within the bank’s existing architecture, from prototyping all the way to production.
Our teams write clear and well-structured technical model documentation to ensure models are unambiguous and well understood throughout the bank.
Our experienced teams assist in efficiently liaising between model developers and model validators to reduce the time and effort required to onboard new models.
We support banks in validating models, both independently and alongside internal validation teams, which brings external experience and accelerates the model validation phase.
We develop and implement analytics on top of existing risk architecture to improve the dissemination of information across the bank and allow easier analysis and assessment of risks.
Artificial intelligence (AI) is advancing rapidly, particularly with the emergence of large language models (LLMs) such as Generative Pre-trained Transformers (GPTs). Yet, in quantitative risk
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VaR has been one of the most widely used risk measures in banks for decades. However, due to the non-additive nature of VaR, explaining the causes of changes to VaR has always been
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Challenges with backtesting Expected Shortfall Recent regulations are increasingly moving toward the use of Expected Shortfall (ES) as a measure to capture risk. Although ES fixes many
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Regulatory Landscape Despite a delay of one year, many banks are struggling to be ready for FRTB in January 2023. Alongside the FRTB timeline, banks are also preparing for other
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The EBA has recently published the findings and observations from their TRIM on-site inspections. A significant number of deficiencies were identified and are required to be remediated by
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Under FRTB regulation, PLA requires banks to assess the similarity between Front Office (FO) and Risk P&L (HPL and RTPL) on a quarterly basis. Desks which do not pass PLA incur capital
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Non-modellable risk factors (NMRFs) have been shown to be one of the largest contributors to capital charges under FRTB. The use of proxies is one of the methods that banks can employ to
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Under the FRTB internal models approach (IMA), the capital calculation of risk factors is dependent on whether the risk factor is modellable. Insufficient data will result in more
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Challenges with VaR models in a turbulent market With recent periods of market stress, including COVID-19 and the Russia-Ukraine conflict, banks are finding their VaR models under
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The Covid-19 pandemic triggered unprecedented market volatility, causing widespread failures in banks' internal risk models. These backtesting failures threatened to increase capital
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In a continued effort to ensure we offer our customers the very best in knowledge and skills, Zanders has acquired Fintegral.
In a continued effort to ensure we offer our customers the very best in knowledge and skills, Zanders has acquired RiskQuest.
In a continued effort to ensure we offer our customers the very best in knowledge and skills, Zanders has acquired Optimum Prime.
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