Lingling Xu

I’m a quantitative analytics professional with 10+ years of experience in consumer credit risk, mortgage valuation, cash flow forecasting, stress testing, and scalable analysis. My work centers on loan-level default and delinquency dynamics, including cohort/vintage and scenario analysis for large consumer portfolios.

I build analytical tools for portfolio surveillance, performance monitoring, and asset quality trend change—so stakeholders can move from complex credit behavior to practical, model-driven decision frameworks. I’ve developed state-transition (Markov) and hazard-based approaches to capture risk migration mechanics across delinquency buckets and translate them into cashflow, loss, and revenue projections.

In my current role, I develop “waterfall style” consumer credit card state transition models and translate business strategies and policy changes into scalable production analytics, including data architecture for Custom Payment Plan programs. I also partner with Model Risk Management to validate model design, assumptions, and performance, strengthening both rigor and operational reliability.

Previously, at a mortgage-focused organization, I performed mortgage portfolio valuation and cash flow forecasting to support pricing, risk assessment, and hedge performance. I automated ETL and analytics workflows and built regression-based forecasting models with performance comparable to vendor solutions, improving efficiency and data integrity.