Work · Dec 2023 — Present · Shenzhen

Turning analysisinto lending decisions

Credit Risk Strategy Analyst
  • Credit policy
  • Regional portfolio
  • External data
  • SQL
  • Python

I work on the decisions behind car financing: who qualifies, how much they pay upfront, and when collateral is required, balancing business growth, access to financing and the risk of customers being unable to repay.

I investigate performance with SQL and Python, turn findings into recommendations, and follow decisions through testing, rollout and monitoring.

Case studies · 04

Four decisions, from question to result

Across all four, the same loop: what needs investigation, which evidence matters, what should change, and how to check the result.

  1. 01Credit policy 8% Share approved for down payments of 20% or less Designing a segmented down-payment policy Rebuilt the policy matrix, then adjusted for conversion and risk to evaluate old-to-new transitions before rollout. Same-applicant comparison against a simulated old policy. Read the case →
  2. 02Regional strategy 463 brand–city combinations reviewed Regional risk evaluation & differentiated strategy A quarterly brand–city evaluation whose classifications shaped differentiated credit policy — from recommendation and approval to improvement targets and review. Read the case →
  3. 03External data 60+ external data products evaluated Evaluating external data sources Evaluated whether external signals offered credible evidence and a useful role in lending decisions. Read the case →
  4. 04Credit policy 8.2% Pre-approved → final review within 10 days: 73.0% vs 64.8% Refining collateral exemptions Used earlier loan-intention information to refine collateral eligibility. New flow vs old flow, observed comparison. Read the case →