William Sanchez Email & Phone Number

Madrid, Es

Madrid, Spain

• Development and validation of credit risk parameters (PD, LGD, CCF/EAD) used to estimate provisions in accordance with IFRS 9 and internal capital (regulatory and/or economic) in accordance with solvency regulations.• Development of internal rating and scoring models to differentiate customer and transaction risk. These models can incorporate Machine Learning algorithms such as Random Forest, XGBoost, Light GBM, CatBoost and neural networks to estimate PD and obtain a scorecard. • Development of attribution and decision support models, such as time series models (SARIMAX) to predict overdue payments (30, 60, 90 and 120 days) for any credit product on the basis of explicative variables (internal and macroeconomic).• Support in the implementation of new regulations: Basel III, Basel IV, IFRS 9, TLAC, stress testing, governance, SREP, etc.• Definition and implementation of periodic stress tests/back tests and updating of recovery plans in banking institutions.• Developing specific models for managing and dealing with regulatory issues, such as sector concentration models.• Methodological, technical and standards monitoring and R&D work. • Continuous advanced training in credit risk modelling, quantitative finance and data science through Afi Escuela's training programmes.

Madrid, Communauté De Madrid, Espagne

● Production of monthly data for Retail, Corporate, Leasing, Cstock and Banks via SQL, PL/SQL and SAS.● Updating the methodology for calculating risk-weighted assets (RWA of €7,000m) and provisions in line with regulatory changes to the new definition of default NDOD, IFRS 9, IFRS 9 forward (in 2024).● Contribution to the optimisation of RWAs using securitisation operations and analysis of their impact.● Implementation and development of Basel III data quality control models using SAS, SQL and VBA.● Production of the ICAAP Spain annual report: stress test of RWAs and macroeconomic variables over 3 years.● Analysis of Tier 1, Tier 2 and Core Tier 1 solvency ratios in relation to Basel III regulations.● Customer data management project in relation to GDPR regulations using Python.● Assessment of accounting reconciliation risk using a macro based on FINREP codes.● Analysis of the results of RWA calculations and projections, using PD, LGD and EAD parameters, following the IRBA and the standardized approach.

Rueil-Malmaison, Île-De-France, France

● Implementation of ML K-means and DBSCAN models with a maximum score of 75.45% via Python, with the aim of identifying high risk Journal Entries. SAP monthly extraction, dataset of 1,700,000 rows and 52 columns. ● Innovation research through NLP models, Deep Learning with NLTK and TensorFlow. ● Project manager for dashboard migration from Microstrategy to Power BI for the Corporate Internal Control team. ● Automation of customer receivables reporting. VBA and Robot Process Automation methods, Uipath. ● Development of a VBA macro to review the outputs of various Danone employees. Share and SAP database.● Facilitation of Power BI training workshop for the French internal control team.

Paris La Défense

● Prospecting and project management for the creation of a software for a naturopath, with SQL and C#.● Management of two consultants and the client for a study valued at 2500 euros, during 6 months.● Participation in the final of the Best Junior Achievement Award, 2 years in a row. ● Participation in Junior Enterprise seminars.

Paris La Défense

Engineering Degree, Financial Engineering, Capital Market Finance

Activities and Societies: Advanced Probability, Stochastic Calculus, Cryptocurrencies Market, Financial Concepts, Machine Learning.

Preparation Classes

Activities and Societies: Mathematics, physics, computer science, engineering sciences3 years dedicated to preparing for the entrance.