Larry
Quantitative Risk Manager @Bank Anonymous
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WORK HISTORY
Quantitative Risk Manager @Bank Anonymous
GB
Established the Model Risk Management (MRM) Framework from the ground up, covering policy development, governance structures, and all core prerequisites: a robust model inventory, comprehensive data dictionaries, and a materiality-tiering framework. Worked with I.T. to design and develop an SQL database (including governance and cybersecurity interests). Escalated critical flaws in a multi-year Strategic Banking Solution programme, prompting CRO intervention and the termination of a contract involving 70+ consultants.Led model risk work on a £XX.Xbn (redacted) debt deal, delivering validation outcomes directly to Senior Management ahead of the Investment Committee (IC).Delivered technical training on MRM, Model Performance Monitoring, VaR, CVaR/Expected Shortfall, and Monte Carlo simulation methodologies, with all computational elements implemented in Python.Supported Balance Sheet Management (IRRBB) initiatives and contributed to the formalisation of ALCO framework and processes.Reviewed a Low-Default Portfolio Econometric PD Proxy Model, identifying weaknesses and coordinating remediation with the external model developer. This included testing of Numerical Methods (Newton-Raphson Algorithm).Used Bloomberg Terminal and quantitative pricing techniques (including Black–Scholes for vanilla benchmarks) to assess and challenge non-vanilla derivative valuations, escalating an issue where Front Office implied volatility assumptions were misaligned with market-implied levels.Maintained and developed cross-platform command-line capability, working across PowerShell/Windows Terminal and Artix Linux/Bash.Continued learning by reading:Vanden Broucke, S. and Baesens, B.(2021) Managing Model Risk: Lessons and experiences from industry and research on the challenges and dangers of analytical models.Scandizzo, S.(2016) The Validation of Risk Models: A Handbook for Practitioners.Le Gall, J-F.(2022) Measure Theory, Probability, and Stochastic Processes.
EDUCATION
King Edward VI College, Stourbridge
A-levels
University of Birmingham
Bachelor of Science - BS, B.Sc. Economics with Honours
ABOUT LARRY
Subject Matter Expert in Model Risk Management with 6+ years’ experience in UK financial services, covering the full model lifecycle: data sourcing and preparation, analytics, model development, independent validation, reverse engineering, and strategic model risk oversight. My experience spans across:Advanced Mathematics/Statistics- Econometrics- Time Series Analysis (ARIMA/GARCH/SARIMAX)- Value at Risk (VaR)- Conditional Value at Risk (CVaR)| Expected Shortfall (ES)- Cox Proportional Hazards Regression (Survival Analysis)- Markov Chains- Numerical Methods (Newton-Raphson algorithm)- Monte Carlo Simulations- Copulas- Taylor Series Expansion- Static Optimisation (Lagrangian)- Dynamic Optimisation (Hamiltonian)- Linear Algebra & Matrix Computations- Hypothesis Testing / Goodness-of-Fit (KS, AUC, PSI/CSI).Computer Science- Python (OOP, NumPy, pandas, SciPy, statsmodels)- Model Development & Validation in SAS- SQL (database design + optimisation)- Linux (Artix) & Bash Scripting- Vim- Version Control (Git/GitLab)- Powershell scripting- Data Structures & Algorithms- Cloud computing- Bloomberg Terminal (including BQuant).Finance- Preparing for the GARP FRM exams- Market Risk (VaR/ES backtesting)- Monetary History- Economics of Banking- Economics of Financial Markets- Modern Portfolio- Advanced Macroeconomics- Game Theory- Discounted Cash Flow modelling- Derivatives / Options- Stressed Capital & ICAAP- Economic Capital & Basel 3.1 / IRRBB / CSRBB.Governance- Ensuring regulatory compliance through statistical rigour and analytics- Design and implementation of Model Risk Management Framework and associated policies- Design and implementation of Model Inventory, Model Materiality Matrix and Tiering Process- Risk Ambassador & Model Risk Oversight Committee (MROC) secretariat- Set up and monitored Key Risk Indicators (KRIs).In parallel to my technical work, I translate complex quantitative concepts into clear insights for senior stakeholders, enabling timely and well-informed decision-making. This includes presenting model performance and risk MI at Committees; one-to-one briefings with senior stakeholders; delivering targeted training; and mentoring new analysts to uplift modelling capability across the enterprise. Beyond modelling, I drive commercial outcomes through vendor procurement in banking systems and data provision, and I actively support talent assessment by interviewing candidates for our graduate programme.
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