Fernando Zelada Maguiña Email & Phone Number

San Diego, California, United States

• Support portfolio managers in liquidity management, risk analysis, and pacing for evergreen funds by constructing tailored portfolios to meet diverse client needs and risk/return profiles.• Develop automated reporting tools in Python, R, Excel, and SQL to streamline insights and enhance data-driven decision-making.• Collaborate on projects leveraging Generative AI models and cutting-edge tools to streamline processes and enhance operational efficiency within the organization.• Enhanced question-answering accuracy for Request for Proposal (RFPs) reports from 40% to 85% by utilizing LLM and embedding models. • Conducted rigorous testing of generative AI models, employing prompt engineering techniques to increase in-house chatbot accuracy utilizing Python.

San Diego, California, United States

• Gathered and analyzed unstructured private markets data (1M+ rows) from various internal sources using MySQL, Excel, R and Python.• Performed portfolio analysis using R and Python, identifying significant trends and recommendations for allocation targets over time.• Created Power BI dashboards using Django API data, applying DAX formulas and Power Query for portfolio fund performance tracking.• Enhanced Pacing cash flow forecasting model, fine-tuning parameters across 40+ investment strategies, and boosting performance by 10%.

San Diego, California, United States

• Analyzed transaction-level customer purchase data to identify and predict B2B customers' purchase patterns, enhance the pricing algorithm, and effectively employ the findings during deal renewal negotiations to optimize pricing strategies.• Engineered Random Forest and XGBoost Machine Learning models to forecast monthly ink and toner cartridge purchases within B2B deals, achieving notable prediction metrics of 85% accuracy for the XGBoost Classifier and 8 RMSE for the Random Forest Regressor. • Levered purchase predictions to conduct sensitivity analysis on discounts and assess the effect of providing higher discounts to customers with a propensity for consistent but smaller purchases, enhancing the B2B pricing recommendation system and boosting gross margin.

San Isidro, Lima, Perú

• Designed and implemented continuous improvement initiatives related to market, structural, and counterparty risk processes, in coordination with other areas: Finance, Global Markets, and Corporate & Investment Banking; in order to reduce reprocesses by more than 60% and to improve the quality of the services delivered (reports, analytical tools, diagnostic analysis, etc.).• Managed and led a squad team to create the Center of Excellence of Reporting in the Risk Area, through implementing informational processes optimization of all the teams using Python and SQL to automate data acquisition, processing, and reporting; increasing efficiency, and saving more than 40 hours of manual effort per month.• Led a cross-functional analytics team to review the E2E process of developing credit risk analytic models, identified and developed initiatives to reduce in 6 months the time-to-market to implement a risk analytical model in coordination with different teams across the bank: Data Engineering, Solutions Development, Risk Analytics (Data Analysts, Data Scientists), and Internal Validation.

San Isidro, Lima, Perú

• Led and implemented continuous improvement initiatives in collection, recovery, and risk monitoring processes; through automation, process reengineering, productivity, and demand management models. As a result, clients’ satisfaction evaluation through the Net Promoter Score (NPS) increased by 53% in six months, and productivity indicators improved by more than 50%. • Designed and automated Dashboards using Google Data Studio and Google Apps Script to measure the impact of the improvements in productivity, quality, time-to-market, and risk control indicators. Before the KPIs Dashboards implementation, less than 20% of the Risk Area teams used a tool to assess their performances and behaviors. • Supported and developed the transformation model that looks for implementing an Operational Center of Excellence into the Risk Area, working with agile methodologies. In order to measure the evolution degree, a Maturity Model was developed, and the efficiency and productivity initiatives increased the Peruvian Risk Area maturity ratio from 47% in Dic. 2019 to 70% in Dic. 2020. This ratio was the most significant annual increase among all the Risk areas in the 7 different countries where BBVA had a presence.• Led an interdisciplinary team of 7 people across the bank in order to work on projects that developed, implemented, and reformulated processes related to risk management and measurement with an end-to-end vision. A relevant project implemented the new processes of provisions and regulatory capital measurement, guarantees application, and recovery of credits covered by Peruvian government funds (FAE and Reactiva Perú) in 3 months after declaring the COVID-19 pandemic. Such implementation allowed the bank’s systems to operate in 2 months, helping the commercial team to save more than USD 3 MM in provision expenses, and reducing delinquent debt in USD 8 MM.

San Isidro, Lima, Perú

• Created a new Monitoring Dashboard with information about the controls within the Wholesale Credit Risk Department: delegation use, rescheduling, and enterprise rating. As a consequence, the controls’ alerts decreased nearly 80% from Oct. 2018 to Oct. 2019.• Evaluated critical risks and supervised action plans based on the Sox and No-Sox control model. As a result, the control framework in the different risk teams improved; thus, it was possible to correct 20 observations identified in previous assessments, to execute a key risk indicator monitoring system, and successfully implement more than 30 action plans related to risk measurement, reporting, and enterprise credit risk admission.• Coordinated and implemented initiatives developed in Holding (Spain), all within the scope of the Governance of Committees celebrated in the Peruvian Risk Area. These initiatives improved the internal organization in the Risk Area by simplifying 18 committees to 10 different focused committees, saving unnecessary time invested in attending other meetings. Besides, the policy and norm approval procedure was defined, which reduced documentary reviews from 2 weeks to 3 days. Due to this, our team was awarded as the area with the best implementation of the governance model in 2019.

Miraflores, Lima, Perú

• Developed, automated, and implemented efficient ETL processes in order to generate monitoring and control reports for credit risk and collection indicators of the microfinance loans portfolio. They were made by gathering, cleaning, and processing data using SQL Server, Visual Studio, and Visual Basic for Excel, reducing more than 1 hour of the operative management reporting time per day and increasing the available time for a more detailed analysis and project participation.• Monitored the commercial team collection management and identified strategies to solve clients' monthly default problems presented in Collection and Mitigation Committees. The strategies implemented helped more than 2,000 clients with credit problems and decreased the delinquency ratio from 4.70% to 3.75% in four months.• Supervised data quality from different information sources (SQL tables, Access databases, etc.). As a result, the number of reports with errors was reduced to zero in two months.• Provided support in the design, calibration, and monitoring of scoring and collection models for the Microfinance loans portfolio.

Miraflores, Lima, Perú

• Designed and automated credit risk monitoring and control indicators reports and dashboards for the microfinance loans portfolio, using SQL, Visual Studio, and Visual Basic for Excel. The automation allowed commercial executives to save time accessing reports and dashboards; thus, the number of clients’ visits with delinquent payments increased by 1,800 in six months.• Led and supervised pilot project implementations in the Microfinance Credit Risk Department, including collection management of SMEs credits. One of the pilot projects was implementing a collection team in 6 of the bank’s microfinance agencies for 3 months. As a result, the pilot agencies’ delinquency ratio was 60% lower than the other agencies’ ratio; and the pilot agencies’ provision expenses were reduced in approximately PEN 1 MM, while in the other forty agencies, the provision expenses’ reduction was almost PEN 300,000 in the same period.• Developed strong data quality rules and analyzed information that improved credit risk and provision expenses monitoring of the microfinance loans portfolio and quickly identified data quality errors. After 3 months of work, the number of reprocesses in the informational process reduced from 3 per day to a maximum 4 per month.• Improved a tool developed in Java that controlled the adequate granting of credit exceptions requested by the commercial. The percentage of observations and alerts reduced by more than 50% in the three months after the implementation.• Supported in the Microfinance statistical score models development and monitoring.

Miraflores, Lima, Perú

Internship in the different areas of the bank and the companies of Pichincha Group (Diners Club, Crecer Seguros and Carsa).• Supported in the different activities developed in each area, in constant coordination with the Managers and Heads.• Generated project proposals that made a positive impact on the organization.• Developed an allocation of provisioning expenses model among the bank's Microfinance agencies as part of my work in the Microfinance Risks area.• Redesigned the treasury fit management model, and elaborated its respective manual.

Av. El Derby 055 Torre 3, Santiago De Surco, Lima, Perú

Supported the Investment Risks Internal Control area, responsible of the following activities:• Investment process operations control: - Previous records of investment orders. - Operations between funds. - Trading autonomies between funds. - Pending trades. - Calls listening from the investment desk and the Back Office.• Fixed income and equity investment prices control.• Eligible instruments list updating.• Intermediaries and trading counterparts evaluation.• Risk and Investment policies and norms data base updating.

Rímac, Lima, Perú

• Led the Events and Public Relations area, which has the purpose to develop and organize workshops, trainings, conferences, debates, and other activities that look for the development and integral growth of undergraduate students.

Rímac, Lima, Perú

• Created economic key performance indicators using STATA software, as part of a consulting work for the National Technical Direction for Territorial Demarcation (Presidency of the Council of Ministers).

Lima, Perú

• Course: Econometrics I• Supported with teaching classes, making exams, and qualifying them.

Master Of Science, Business Analytics, 3.9 / 4.0

Activities and Societies: Co-Director Events and Operations | Rady Data Analytics Club (2022 - 2023).• Coursework: - Business Analytics.

Diploma Of Education, Data Science: Machine Learning & Deep Learning With Python

Bachelor Of Science - Bs, Economic Engineering, 4.0 / 4.0

Activities and Societies: Head of the academic area of the Student Center of the Economic and Statistical Engineering Faculty (2013.