Vanessa Feng

2024San Diego

Probability of default model

Project, Jan⁠–⁠May 2024

300 → 10candidate variables cut to the final model

• A logistic-regression model of credit card default. Vintage curves set a 6‑month performance window; roll-rate analysis tracked accounts within it.
• Narrowed the candidate variables with break-and-heal binning, weight of evidence and information value, stepwise regression and cluster analysis.
• Set warning and breach thresholds for ongoing monitoring.

KS

55%

PSI

13%

MAPE

10%

2024San Francisco

Rappo

VC Analyst Intern, Jun⁠–⁠Sep 2024

200+investors pitched with the deck she designed

• Designed the 10+ slide pitch deck Rappo used with 200+ investors to raise its first round.
• Built a database of 500+ target investors with Python and web scraping, with a risk-appetite scorecard for fit that improved targeting accuracy 50%+.
• Mined keywords and language patterns from 50+ VC blogs with the OpenAI GPT API; the resulting content template reached 5,000+ impressions, with 12% conversion and 34% click-through.

2025Greenville

Lima One Capital

Credit Risk Intern, May⁠–⁠Aug 2025

30⁠–⁠35%fewer false positives on the loan watchlist

• Piped the probability‑of‑default model into the watchlist as a loan filter, saving about 10 hours of manual review a month for the Credit and Servicing teams.
• Tested 8 model thresholds against recall, precision, accuracy and ROC‑AUC; chose the one that kept recall above 0.90 with the other metrics at or above firm benchmarks.
• Built Datarails dashboards that segment about 300 flagged loans a month by product, geography, vintage and sponsor.
• Restructured the credit approval memo to quantify risk assessments; approval meetings ran about 50% faster.

2025New York

Morgan Stanley

Wealth Management Intern, Portfolio Risk Management, Aug⁠–⁠Sep 2025

$100MM+in client assets positioned by the team with the Excel forecasts she built

• Tailored model portfolios for six new clients to their risk profiles, liquidity needs and existing exposure, and tested their long-term goals with Monte Carlo simulation.
• Designed duration- and credit-appropriate fixed income strategies for 10+ client portfolio reviews with the financial planning team.
• Screened and modelled 10+ US large- and mid-cap stocks; built the Excel forecasts through 2028 that the team used for tactical positioning of $100MM+ in client assets.
• Assessed 5 private market funds in infrastructure, real estate and private credit for risk and client suitability, supporting asset allocation across 50+ client portfolios.

2026New York

J.P. Morgan

Asset Management Summer Analyst, Jun⁠–⁠Aug 2026

Returns full-time as an Analyst in New York.