Fabiola Grace

Background

About Fabiola Grace

I bring professional experience and an academic background that place me at the intersection of finance and data. I’ve worked across financial services, capital markets, and insurance, with roles as an actuary, data scientist, and equity researcher. Now, I focus on credit risk — bringing a rigorous, end-to-end quantitative lens to risk measurement and decisioning. With a Master of Management Analytics, B.Sc. in Statistics, and CFA level 1 passed, I bring expertise in AI, machine learning, predictive analytics, market research, and financial modeling. Beyond my professional pursuits, I am a dedicated leader at World Vision, creating fundraising initiatives to support underprivileged children. Key highlights of my experience: Deployed an AI Agent with RAG workflow leveraging three distinct LLM foundational models to analyze annual reports, quantify portfolio risk exposures, and enhance strategic asset allocation. Contributed to financial modeling and equity research reports in sectors such as consumer staples and property, applying advanced valuation methods and quantitative analysis. Competed in portfolio management and data science competitions, including optimizing stock selection through quantitative analytics and analyzing customer retention using attribution modeling. Developed predictive models for fraud detection and financial risk management, utilizing machine learning algorithms (Python, R) to analyze large datasets, enhancing forecast accuracy. Automated financial reporting processes, reducing processing time by 30% with SQL, VBA, and PowerBI, and saving manual labor through workflow optimization. Specialties: Quantitative Finance, Machine Learning, Predictive Modeling, Attribution Modeling, Dashboards, Financial Valuation, Risk Management, and Insurance. Tools: Python, SQL, R, VBA, PowerBI, SAS, Bloomberg Terminal Contact me: fabiolagrace@outlook.com