Heng Yi

Developed and optimized a comprehensive underwriting policy for online machine-based personal unsecured loans, encompassing data preparation, model testing, and performance monitoring.

Executed robust data extraction, transformation, and loading (ETL) processes using SQL and Python, ensuring data integrity for credit policy development and model training.

Designed and implemented multi-factor anti-fraud mechanisms, leveraging data matching and manual verification to significantly mitigate identity theft-related fraud risks.

Developed a proactive risk mitigation strategy during inflation, establishing hard-cut rules based on credit report variables that enhanced underwriting system efficiency.

Collaborated with data scientists to build and integrate risk rating models, focusing on feature engineering and model validation for improved underwriting policy accuracy.

Compiled and structured diverse datasets to support data-driven decision-making processes, enhancing strategic insights.

Developed an advanced analytical model in Excel, utilizing collected data to generate actionable strategic recommendations for business growth.

Secured over $200,000 in investment through strategic planning and persuasive presentations, directly contributing to company expansion.

Utilized Excel and financial software to perform in-depth analysis of loan portfolio data, identifying key trends and risk factors.

Assisted in evaluating loan applications, analyzing financial statements, credit reports, and business plans to assess borrower risk comprehensively.

Conducted fundamental financial analysis, including debt-to-income ratio calculations and cash flow assessments, to support informed underwriting decisions.

Supported underwriting team operations, ensuring accurate data entry and documentation compliance with regulatory requirements.

Communicated effectively with applicants and relationship managers, streamlining the gathering of necessary documents to facilitate loan approvals.

Collaborated with senior underwriters to enhance credit risk assessment procedures and improve overall underwriting efficiency.