Global Subject Matter Experts

Quantitative Risk Analytics, XVA & Regulatory Capital - Independent Consultants

Subject Matter Experts


Ignacio Ruiz and Mariano Zeron provide independent consulting services in Quantitative Risk Analytics, CVA, FVA, KVA, regulatory capital and other related topics. They are highly delivery orientated.

Ignacio has a proven track record at designing risk methodologies, building risk analytics frameworks and managing projects to completion in tier-1 investment banks. Previous to establishing himself independently, he was the head strategist for Counterparty Risk exposure measurement at Credit Suisse, and the head of Equity Risk Methodology at BNP Paribas. He holds a PhD in nano-physics from Cambridge University.

Mariano is a leading quant in the topic of risk engine acceleration, with several papers and presentations on the topic. He has implemented risk engine accelerators in tier-1 banks like HSBC or Nomura.

Key areas of expertise include:

Counterparty Credit Risk Analytics

Risk Factor Evolution Risk metrics: PFE, EPE, cPFE Model, Calibration, Pricing within MC simulation, Model Backtesting, Regulatory Capital Calculation   MORE  

XVA pricing

CVA, FVA, & KVA pricing, Credit Spread curve proxy, Delta Hedging, Integration with Risk function   MORE  

Market Risk Analytics

VaR, ES, Parametric Monte Carlo and Historical Simulation, Advanced Methodologies, Validation   MORE  

Project Delivery, Internal Governance & Regulatory

IMM capital applications, Coordination, Methodology, Risk Management and Systems, Internal Governance processMORE  

Experts in Risk Analytics – publication:


Denting the FRTB IMA computational challenge via Orthogonal Chebyshev Sliding Technique

In this paper we introduce a new technique based on high-dimensional Chebyshev Tensors that we call Orthogonal Chebyshev Sliding Technique. We implemented this technique inside the systems of a tier-one bank, and used it to approximate Front Office pricing functions in order to reduce the substantial computational burden associated with the capital calculation as specified by FRTB IMA. In all cases, the computational burden reductions obtained were of more than 90%, while keeping high degrees of accuracy, the latter obtained as a result of the mathematical properties enjoyed by Chebyshev Tensors.

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